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Thematische Bibliographien / Transformation of image / Zeitschriftenartikel

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Zeitschriftenartikel zum Thema „Transformation of image“

Autor: Grafiati

Veröffentlicht am 28. Juni 2021

Zuletzt aktualisiert am 29. Juli 2025

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1

Kim, J., T. Kim, D. Shin, and S. H. Kim. "ROBUST MOSAICKING OF UAV IMAGES WITH NARROW OVERLAPS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 6, 2016): 879–83. http://dx.doi.org/10.5194/isprs-archives-xli-b1-879-2016.

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This paper considers fast and robust mosaicking of UAV images under a circumstance that each UAV images have very narrow overlaps in-between. Image transformation for image mosaicking consists of two estimations: relative transformations and global transformations. For estimating relative transformations between adjacent images, projective transformation is widely considered. For estimating global transformations, panoramic constraint is widely used. While perspective transformation is a general transformation model in 2D-2D transformation, this may not be optimal with weak stereo geometry suc

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Kim, J., T. Kim, D. Shin, and S. H. Kim. "ROBUST MOSAICKING OF UAV IMAGES WITH NARROW OVERLAPS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 6, 2016): 879–83. http://dx.doi.org/10.5194/isprsarchives-xli-b1-879-2016.

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This paper considers fast and robust mosaicking of UAV images under a circumstance that each UAV images have very narrow overlaps in-between. Image transformation for image mosaicking consists of two estimations: relative transformations and global transformations. For estimating relative transformations between adjacent images, projective transformation is widely considered. For estimating global transformations, panoramic constraint is widely used. While perspective transformation is a general transformation model in 2D-2D transformation, this may not be optimal with weak stereo geometry suc

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Sempio, J. N. H., R. K. D. Aranas, B. P. Lim, B. J. Magallon, M. E. A. Tupas, and I. A. Ventura. "ASSESSMENT OF DIFFERENT IMAGE TRANSFORMATION METHODS ON DIWATA-1 SMI IMAGES USING STRUCTURAL SIMILARITY MEASURE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W19 (December 23, 2019): 393–400. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w19-393-2019.

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Abstract. This paper aims to provide a qualitative assessment of different image transformation parameters as applied on images taken by the spaceborne multispectral imager (SMI) sensor installed in Diwata-1, the Philippines’ first Earth observation microsatellite, with the aim of determining the order of transformation that is sufficient for operationalization purposes. Images of the Palawan area were subjected to different image transformations by manual georeferencing using QGIS 3, and cloud masks generated and applied to remove the effects of clouds. The resulting images were then subjecte

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Jabir, Adnan. "Image Geometrical Analogies." Journal of Al-Rafidain University College For Sciences ( Print ISSN: 1681-6870 ,Online ISSN: 2790-2293 ), no. 2 (October 26, 2021): 113–30. http://dx.doi.org/10.55562/jrucs.v23i2.484.

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Geometric transform (G.T.) of images is a critical operation in commercial television, film producing and advertisement design. All geometric transformation operations are performed by moving pixel values from their original spatial coordinates to new coordinates in the destination image. The traditional algorithms for geometric transformation are time consuming and not accurate. With a very few exceptions, all geometric transformations result in some output pixel locations being missed because no input pixels were transformed there. This paper presents an easy-to- implement and very efficient

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Garg, Ankit, Ashish Negi, and Geeta Chauhan. "Analysis of Iterated Affine Transformation Function and Linear Mapping for Content Preservation." International Journal of Engineering & Technology 7, no. 4.19 (2018): 50–57. http://dx.doi.org/10.14419/ijet.v7i4.19.22014.

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In image scaling contents of image can be distorted which are required to preserve using linear mapping. Geometric transformations can preserve structural properties i.e. parallelism, colinearity and orientation. It is highly desirable to preserve structural properties of image contents because human visual system is very sensitive to distortion of objects. In this paper image scaling is performed using iterative affine transformation and results show that linear mapping function applied on affine space preserve affine properties under affine transformation. A number of scaling operations are

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Kim, Jae-In, Hyun-cheol Kim, and Taejung Kim. "Robust Mosaicking of Lightweight UAV Images Using Hybrid Image Transformation Modeling." Remote Sensing 12, no. 6 (2020): 1002. http://dx.doi.org/10.3390/rs12061002.

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This paper proposes a robust feature-based mosaicking method that can handle images obtained by lightweight unmanned aerial vehicles (UAVs). The imaging geometry of small UAVs can be characterized by unstable flight attitudes and low flight altitudes. These can reduce mosaicking performance by causing insufficient overlaps, tilted images, and biased tiepoint distributions. To solve these problems in the mosaicking process, we introduce the tiepoint area ratio (TAR) as a geometric stability indicator and orthogonality as an image deformation indicator. The proposed method estimates pairwise tra

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Liu, Hongbing, Gengyi Liu, Xuewen Ma, and Daohua Liu. "Training dictionary by granular computing with L∞-norm for patch granule–based image denoising." Journal of Algorithms & Computational Technology 12, no. 2 (2018): 136–46. http://dx.doi.org/10.1177/1748301818761131.

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Considering the objects by different granularity reflects the recognition common law of people, granular computing embodies the transformation between different granularity spaces. We present the image denoising algorithm by using the dictionary trained by granular computing with L∞-norm, which realizes three transformations, (1) the transformation from image space to patch granule space, (2) the transformation between granule spaces with different granularities, and (3) the transformation from patch granule space to image space. We demonstrate that the granular computing with L∞-norm achieved

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MAZURETS, O., T. SKRYPNYK, and A. IZOTOV. "FACET METHOD OF IMAGE TRANSFORMATION BY MEANS OF NEURAL NETWORK RECOGNITION." Herald of Khmelnytskyi National University. Technical sciences 281, no. 1 (2020): 147–53. https://doi.org/10.31891/2307-5732-2020-281-1-147-153.

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The method of facet image conversion is a software resizing of the input image and is intended for use in the process of image recognition. Based on the developed facet method for image transformation, an application was created for neural network image recognition after processing by the developed method. To investigate the efficiency of the facet image conversion method, the results of the image recognition were compared before and after the facet image convolution. The developed facet image convolution information technology uses the facet image conversion method and allows the image to be

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Sarid, Orly, and Ephrat Huss. "Image formation and image transformation." Arts in Psychotherapy 38, no. 4 (2011): 252–55. http://dx.doi.org/10.1016/j.aip.2011.07.001.

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Liu, Jincheng. "Keywords-based conditional image transformation." Applied and Computational Engineering 57, no. 1 (2024): 56–65. http://dx.doi.org/10.54254/2755-2721/57/20241310.

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In recent years, Generative Adversarial Networks (GANs) and their variants, such as pix2pix, have occupied a significant position in the field of image generation. Despite the impressive performance of the pix2pix model in image-to-image transformation tasks, its reliance on a large amount of paired training data and computational resources has posed a crucial constraint to its broader application. To address these issues, this paper introduces a novel algorithm, Keywords-Based Conditional Image Transformation (KB-CIT). KB-CIT dynamically extracts keywords from the input grayscale images to ac

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G., Sindhu Madhuri, and Indra Gandhi M. P. "New Image Registration Techniques: Development and Comparative Analysis." International Journal of Emerging Research in Management and Technology 6, no. 7 (2018): 146. http://dx.doi.org/10.23956/ijermt.v6i7.204.

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Design and Development of new Image Registration Techniques by using complex mathematical transformation functions are attempted in this research work as there is a requirement for the performance measurement of image registration complexity. The design and development of new image registration techniques are carried out with complex mathematical transformations of Radon and Slant functions due to their importance. And the rotation and translation geometric function are considered for better insight into the complex image registration process. The newly developed image registration techniques

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Smagina, O. A. "The Image of Transformation and Cognitive Flexibility." Reflexio 15, no. 2 (2023): 76–86. http://dx.doi.org/10.25205/2658-4506-2022-15-2-76-86.

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The article suggests to view the image of transformation as an idea, that affects cognitive flexibility (the ability to overcome responses or thinking that have become habitual and adapt to new situations). We may notice, that cultural stereotypes of thinking are partly predetermined by mythology. Myths represent our mind’s view of mental capabilities, the way our conscience interprets unconscious processes. The following describes the images of transformations in ancient Greek and Hindu mythologies as two points of view on psychic processes, letting us notice possibilities and limitations of

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Iqbal, Saima, Wilayat Khan, Abdulrahman Alothaim, Aamir Qamar, Adi Alhudhaif, and Shtwai Alsubai. "Proving Reliability of Image Processing Techniques in Digital Forensics Applications." Security and Communication Networks 2022 (March 31, 2022): 1–17. http://dx.doi.org/10.1155/2022/1322264.

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Binary images have found its place in many applications, such as digital forensics involving legal documents, authentication of images, digital books, contracts, and text recognition. Modern digital forensics applications involve binary image processing as part of data hiding techniques for ownership protection, copyright control, and authentication of digital media. Whether in image forensics, health, or other fields, such transformations are often implemented in high-level languages without formal foundations. The lack of formal foundation questions the reliability of the image processing te

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Wang, Nannan, Jie Li, Dacheng Tao, Xuelong Li, and Xinbo Gao. "Heterogeneous image transformation." Pattern Recognition Letters 34, no. 1 (2013): 77–84. http://dx.doi.org/10.1016/j.patrec.2012.04.005.

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Dixit, Karnika, and Mr Kamlesh Lakhwani. "A NOVEL METHOD OF COLOR IMAGE ENHANCEMENT BY COLOR SPACE TRANSFORMATION FOLLOWED BY GAMMA/LOGARITHMIC TRANSFORMATION." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 8, no. 1 (2013): 707–11. http://dx.doi.org/10.24297/ijct.v8i1.3430.

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Visual enhancement of image plays a very important role in the field of medical imaging. Enhanced medical images are more suitable for analysis and proper diagnosis. We present a novel method of enhancement of color medical images in this paper. We are transforming color space of the image from RGB to HIS followed by application of logarithmic and gamma transformation on saturation and intensity component respectively. Hence we obtain a visually enhanced version of the original image. We have obtained excellent color medical image enhancement results presented in this paper.

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Golub, Yu I. "COMPRESSION OF HIGH DYNAMIC RANGE OF SAR IMAGES." «System analysis and applied information science», no. 1 (June 12, 2018): 51–57. http://dx.doi.org/10.21122/2309-4923-2018-1-51-57.

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The paper presents results of our experiments on compression of the high dynamic range SAR images. The range is equal to 16-bit. Objectives of study were comparison of known approaches to compression of the high dynamic range images; selection of optimal parameters for compression algorithms, and selection of a no-reference measure for image quality assessment after compression. Tone-mapping transformations like gamma correction, Ashikhmin-operator, mu-transformation, as well as no-reference image quality assessment measures were tested. The results of the experiments are presented in the arti

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Xu, Pengcheng, Qingnan Fan, Fei Kou, et al. "Textualize Visual Prompt for Image Editing via Diffusion Bridge." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 20 (2025): 21779–87. https://doi.org/10.1609/aaai.v39i20.35483.

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Visual prompt, a pair of before-and-after edited images, can convey indescribable imagery transformations and prosper in image editing. However, current visual prompt methods rely on a pretrained text-guided image-to-image generative model that requires a triplet of text, before, and after images for retraining over a text-to-image model. Such crafting triplets and retraining processes limit the scalability and generalization of editing. In this paper, we present a framework based on any single text-to-image model without reliance on the explicit image-to-image model thus enhancing the general

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WANG, XIUYING, and DAVID DAGAN FENG. "AUTOMATIC ELASTIC MEDICAL IMAGE REGISTRATION BASED ON IMAGE INTENSITY." International Journal of Image and Graphics 05, no. 02 (2005): 351–69. http://dx.doi.org/10.1142/s0219467805001793.

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An automatic elastic medical image registration approach is proposed, based on image intensity. The algorithm is divided into two steps. In Step 1, global affine registration is first used to establish an initial guess and the resulting images can be assumed to have only small local elastic deformations. The mapped images are then used as inputs in Step 2, during which, the study image is modeled as elastic sheet by being divided into sub-images. Moving the individual sub-image in the reference image, the local displacement vectors are found and the global elastic transformation is achieved by

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Hou, Dongdong, Weiming Zhang, and Nenghai Yu. "Image camouflage by reversible image transformation." Journal of Visual Communication and Image Representation 40 (October 2016): 225–36. http://dx.doi.org/10.1016/j.jvcir.2016.06.018.

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Huang, Hung-Tsai, Zi-Cai Li, Yimin Wei, and Ching Yee Suen. "Improved Splitting-Integrating Methods for Image Geometric Transformations: Error Analysis and Applications." Mathematics 13, no. 11 (2025): 1773. https://doi.org/10.3390/math13111773.

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Geometric image transformations are fundamental to image processing, computer vision and graphics, with critical applications to pattern recognition and facial identification. The splitting-integrating method (SIM) is well suited to the inverse transformation T−1 of digital images and patterns, but it encounters difficulties in nonlinear solutions for the forward transformation T. We propose improved techniques that entirely bypass nonlinear solutions for T, simplify numerical algorithms and reduce computational costs. Another significant advantage is the greater flexibility for general and co

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Fida, A. D., A. V. Gaidel, N. S. Demin, N. Yu Ilyasova, and E. A. Zamytskiy. "Automated combination of optical coherence tomography images and fundus images." Computer Optics 5, no. 45 (2021): 721–27. http://dx.doi.org/10.18287/2412-6179-co-892.

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We discuss approaches to combining multimodal multidimensional images, namely, three-dimensional optical coherence tomography (OCT) data and two-dimensional color images of the fundus. Registration of these two modalities can help to adjust the position of the obtained OCT images on the retina. Some existing approaches to matching fundus images are based on finding key points that are considered invariant to affine transformations and are common to the two images. However, errors in the identification of such points can lead to registration errors. There are also methods for iterative adjustme

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Fida, A. D., A. V. Gaidel, N. S. Demin, N. Yu Ilyasova, and E. A. Zamytskiy. "Automated combination of optical coherence tomography images and fundus images." Computer Optics 5, no. 45 (2021): 721–27. http://dx.doi.org/10.18287/2412-6179-co-892.

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We discuss approaches to combining multimodal multidimensional images, namely, three-dimensional optical coherence tomography (OCT) data and two-dimensional color images of the fundus. Registration of these two modalities can help to adjust the position of the obtained OCT images on the retina. Some existing approaches to matching fundus images are based on finding key points that are considered invariant to affine transformations and are common to the two images. However, errors in the identification of such points can lead to registration errors. There are also methods for iterative adjustme

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Mat Jizat, Jessnor Arif, Ahmad Fakhri Ab. Nasir, Anwar P.P Abdul Majeed, and Edmund Yuen. "Effect of Image Compression using Fast Fourier Transformation and Discrete Wavelet Transformation on Transfer Learning Wafer Defect Image Classification." MEKATRONIKA 2, no. 1 (2020): 16–22. http://dx.doi.org/10.15282/mekatronika.v2i1.6704.

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Automated inspection machines for wafer defects usually captured thousands of images on a large scale to preserve the detail of defect features. However, most transfer learning architecture requires smaller images as input images. Thus, proper compression is required to preserve the defect features whilst maintaining an acceptable classification accuracy. This paper reports on the effect of image compression using Fast Fourier Transformation and Discrete Wavelet Transformation on transfer learning wafer defect image classification. A total of 500 images with 5 classes with 4 defect classes and

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Tan, Daning, Yu Liu, Gang Li, Libo Yao, Shun Sun, and You He. "Serial GANs: A Feature-Preserving Heterogeneous Remote Sensing Image Transformation Model." Remote Sensing 13, no. 19 (2021): 3968. http://dx.doi.org/10.3390/rs13193968.

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In recent years, the interpretation of SAR images has been significantly improved with the development of deep learning technology, and using conditional generative adversarial nets (CGANs) for SAR-to-optical transformation, also known as image translation, has become popular. Most of the existing image translation methods based on conditional generative adversarial nets are modified based on CycleGAN and pix2pix, focusing on style transformation in practice. In addition, SAR images and optical images are characterized by heterogeneous features and large spectral differences, leading to proble

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Awan, Hafiz Shakeel Ahmad, and Muhammad Tariq Mahmood. "Deep Dynamic Weights for Underwater Image Restoration." Journal of Marine Science and Engineering 12, no. 7 (2024): 1208. http://dx.doi.org/10.3390/jmse12071208.

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Underwater imaging presents unique challenges, notably color distortions and reduced contrast due to light attenuation and scattering. Most underwater image enhancement methods first use linear transformations for color compensation and then enhance the image. We observed that linear transformation for color compensation is not suitable for certain images. For such images, non-linear mapping is a better choice. This paper introduces a unique underwater image restoration approach leveraging a streamlined convolutional neural network (CNN) for dynamic weight learning for linear and non-linear ma

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Perju, Veaceslav, and Vladislav Cojuhari. "CENTRAL AND LOGARITHMIC CENTRAL IMAGE CHORD TRANSFORMATIONS FOR INVARIANT OBJECT RECOGNITION." Journal of Engineering Science XXVIII (1) (March 15, 2021): 38–46. https://doi.org/10.52326/jes.utm.2021.28(1).03.

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Pattern descriptors invariant to rotation, scaling, and translation represents an important direction in the elaboration of the real time object recognition systems. In this article, the new kinds of object descriptors based on chord transformation are presented. There are described new methods of image presentation - Central and Logarithmic Central Image Chord Transformations (CICT and LCICT). It is shown that the CICT operation makes it possible to achieve invariance to object rotation. In the case of implementation of the LCICT transformation, invariance to changes in the rotation and scale

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Martinho, Laura, José Pio, and Felipe Oliveira. "Deep Learning-Driven Parameter Adaptation for Underwater Image Restoration." Revista Eletrônica de Iniciação Científica em Computação 22, no. 1 (2024): 81–90. http://dx.doi.org/10.5753/reic.2024.4671.

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In this paper we propose a learning-based approach to enhance underwater image quality by optimizing parameters and applying intensity transformations. Our methodology involves training a CNN Regression model on diverse underwater images to learn enhancing parameters, followed by applying intensity transformation techniques. In order to evaluate our approach, we conducted experiments using well-known underwater image datasets found in the literature, comprising real-world subaquatic images and we propose a novel underwater image dataset, composed by 276 images from Amazon turbid water rivers.

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Wu, Dan. "Reversible Data Hiding for Encrypted Image Based on Arnold Transformation." MATEC Web of Conferences 173 (2018): 03088. http://dx.doi.org/10.1051/matecconf/201817303088.

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A reversible data hiding scheme for encrypted image was proposed based on Arnold transformation. In this scheme, the original image was divided into four sub-images by sampling, the sub-images were scrambled by Arnold transformation using two secret keys, then the scrambled sub-images were reconstituted an encrypted image. Subsequently, additional data was embedded into the encrypted image by modifying the difference between two adjacent pixels. With an encrypted image containing additional data, the receiver can obtain a decrypt image using the decryption key. Meanwhile, with the aid of the d

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Li, Dongyang, Lin Yang, Hongguang Zhang, Xiaolei Wang, Linru Ma, and Junchao Xiao. "Image-Based Insider Threat Detection via Geometric Transformation." Security and Communication Networks 2021 (September 13, 2021): 1–18. http://dx.doi.org/10.1155/2021/1777536.

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Insider threat detection has been a challenging task over decades; existing approaches generally employ the traditional generative unsupervised learning methods to produce normal user behavior model and detect significant deviations as anomalies. However, such approaches are insufficient in precision and computational complexity. In this paper, we propose a novel insider threat detection method, Image-based Insider Threat Detector via Geometric Transformation (IGT), which converts the unsupervised anomaly detection into supervised image classification task, and therefore the performance can be

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Xu, Yihao. "CNN-based image style transformation--Using VGG19." Applied and Computational Engineering 39, no. 1 (2024): 130–36. http://dx.doi.org/10.54254/2755-2721/39/20230589.

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eural Style Transfer is a widely used approach in the field of computer vision, which aims to generate visual effects by integrating the information contained in one image into another. In this paper, this work presents an implementation of neural style transfer using TensorFlow and the VGG19 model. The proposed method involves loading and preprocessing the content and style images, extracting features from both images using the VGG19 model, and computing Gram matrices to capture the style information. A StyleContentModel class is introduced to encapsulate the style and content extraction proc

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Pandurangan, Durai, R. Saravana Kumar, Lukas Gebremariam, L. Arulmurugan, and S. Tamilselvan. "Combined Gray Level Transformation Technique for Low Light Color Image Enhancement." Journal of Computational and Theoretical Nanoscience 18, no. 4 (2021): 1221–26. http://dx.doi.org/10.1166/jctn.2021.9392.

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Insufficient and poor lightning conditions affect the quality of videos and images captured by the camcorders. The low quality images decrease the performances of computer vision systems in smart traffic, video surveillance, and other imaging systems applications. In this paper, combined gray level transformation technique is proposed to enhance the less quality of illuminated images. This technique is composed of log transformation, power law transformation and adaptive histogram equalization process to improve the low light illumination image estimated using HIS color model. Finally, the enh

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Raghawendra, Bhimarao Naik, and N.Kunchur Pavan. "Image Fusion Based on Wavelet Transformation." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 5 (2020): 473–77. https://doi.org/10.35940/ijeat.D9161.069520.

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The article based totally on the MATLAB software program simulation was carried out on the image fusion; to design and develop a MATLAB based image processing application for fusing two images of the similar scene received through other modalities. The application is required to use Discrete Wavelet Transform (DWT) and Pulse Coupled Neural Network (PCNN) techniques. The comparison is to be performed on the results obtained on the above mentioned techniques.

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Hocevar, Erwin, and Walter G. Kropatsch. "Inventing the Formula of the Trees: A Solution of the Representation of Self Similar Objects." Fractals 05, supp01 (1997): 51–64. http://dx.doi.org/10.1142/s0218348x97000632.

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Iterated Function Systems (IFS) seem to be used best to represent objects in the nature, because many of them are self similar. An IFS is a set of affine and contractive transformations. The union (so-called collage) of the subimages generated by transforming the whole image produces the image again - the self similar attractor of these transformations, which can be described by a binary image. For a fast and compact representation of those images, it would be desirable to calculate the transformations (the IFS-Codes) directly from the image that means to solve the inverse IFS-Problem. The sol

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Barthel, Kai Uwe. "Entropy Constrained Fractal Image Coding." Fractals 05, supp01 (1997): 17–26. http://dx.doi.org/10.1142/s0218348x97000607.

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In this paper we present an entropy constrained fractal coding scheme. In order to get high compression rates, previous fractal coders used hierarchical coding schemes with variable range block sizes. Our scheme uses constant range block sizes, but the complexity of the fractal transformations is adapted to the image contents. The entropy of the fractal code can be significantly reduced by introducing geometrical codebooks of variable size and a variable order luminance transformation. We propose a luminance transformation consisting of a unification of fractal and transform coding. With this

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Prakash, S. Om. "IMAGE STEGANOGRAPHY USING MID POINT TRANSFORMATION TECHNIQUE." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem31632.

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The project titled "Image Steganography using Mid-Point Transformation Technique" aims to explore and implement a novel approach to concealing information within digital images while preserving their visual integrity. Steganography is an age-old technique for covert communication, and this project leverages the mid-point transformation method to embed data seamlessly into images. The mid-point transformation technique involves the subtle alteration of pixel values based on the midpoint of neighboring pixels. This process ensures that the changes made to the image are imperceptible to the human

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D, Rajeshwari, Dr Shrinivasa Naika C. L,, and Dr Mohamed Rafi. "LUNG SCANS SEGMENTATION USING MARKER-CONTROLLED WATERSHED TRANSFORMATION." International Journal of Engineering Applied Sciences and Technology 7, no. 3 (2022): 152–56. http://dx.doi.org/10.33564/ijeast.2022.v07i03.024.

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Image segmentation is the process of partitioning a digital image into multiple segments knows as set of pixels. Image segmentation is typically used to locate objects and boundaries (lines, curves, etc.) in images. It is the process of assigning a label to every pixel in an image such that pixels with the same label share certain visual characteristics. The Watershed Transform consists of an image partitioning into its constitutive regions. This transform is easily adapted to be used in different types of images and it allows distinguishing complex objects. The marker watershed transformation

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Deng, Xiaozheng, Shasha Mao, Jinyuan Yang, et al. "Multi-Class Double-Transformation Network for SAR Image Registration." Remote Sensing 15, no. 11 (2023): 2927. http://dx.doi.org/10.3390/rs15112927.

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In SAR image registration, most existing methods consider the image registration as a two-classification problem to construct the pair training samples for training the deep model. However, it is difficult to obtain a mass of given matched-points directly from SAR images as the training samples. Based on this, we propose a multi-class double-transformation network for SAR image registration based on Swin-Transformer. Different from existing methods, the proposed method directly considers each key point as an independent category to construct the multi-classification model for SAR image registr

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Watcharawipha, Anirut, Nipon Theera-Umpon, and Sansanee Auephanwiriyakul. "Space Independent Image Registration Using Curve-Based Method with Combination of Multiple Deformable Vector Fields." Symmetry 11, no. 10 (2019): 1210. http://dx.doi.org/10.3390/sym11101210.

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This paper proposes a novel curve-based or edge-based image registration technique that utilizes the curve transformation function and Gaussian function. It enables deformable image registration between images in different spaces, e.g., different color spaces or different medical image modalities. In particular, piecewise polynomial fitting is used to fit a curve and convert it to the global cubic B-spline control points. The transformation between the curves in the reference and source images are performed by using these control points. The image area is segmented with respect to the referenc

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Minati, Mishra. "IMAGE ENCRYPTION USING FIBONACCI-LUCAS TRANSFORMATION." International Journal on Cryptography and Information Security (IJCIS) 2, no. 3 (2020): 131–41. https://doi.org/10.5281/zenodo.3775563.

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Secret communication techniques are of great demand since last 3000 years due to the need of information security and confidentiality at various levels of communication such as while communicating confidential personal data , patients’ medical data, countries’ defence and intelligence information, data related to examinations etc. With advancements in image processing research, Image encryption and Steganographic techniques have gained popularity over other forms of hidden communication techniques during the last few decades and a number of image encryption models are suggested by

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Zhang, Yu Jun, Mei Xiang, and Ying Tian. "An Efficient Ear Recognition Method from Two-Dimensional Images." Advanced Materials Research 1049-1050 (October 2014): 1531–35. http://dx.doi.org/10.4028/www.scientific.net/amr.1049-1050.1531.

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An efficient ear recognition method by weighted wavelet transformation and Bi-Directional principal component analysis was proposed. First, each ear image was decomposed into four sub-images by wavelet transformation ,the four sub-images were low frequency image , vertical detail image ,horizontal detail image and high frequency image .Then the low frequency image was decomposed into four sub-images, the four-images were weighted by different coefficients, then ,the four sub-images were reconstructed into a image .On this basis ,the feature was extraction by the BDPCA method ,and then we use t

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Fernández, Claudio Ignacio, Ata Haddadi, Brigitte Leblon, Jinfei Wang, and Keri Wang. "Comparison between Three Registration Methods in the Case of Non-Georeferenced Close Range of Multispectral Images." Remote Sensing 13, no. 3 (2021): 396. http://dx.doi.org/10.3390/rs13030396.

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Cucumber powdery mildew, which is caused by Podosphaera xanthii, is a major disease that has a significant economic impact in cucumber greenhouse production. It is necessary to develop a non-invasive fast detection system for that disease. Such a system will use multispectral imagery acquired at a close range with a camera attached to a mobile cart’s mechanic extension. This study evaluated three image registration methods applied to non-georeferenced multispectral images acquired at close range over greenhouse cucumber plants with a MicaSense® RedEdge camera. The detection of matching points

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Joe, G. Saliby. "Design and Implementation of Digital Image Transformation Algorithms." International Journal of Trend in Scientific Research and Development 3, no. 3 (2019): 623–31. https://doi.org/10.31142/ijtsrd22918.

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In computer science, Digital Image Processing or DIP is the use of computer hardware and software to perform image processing and computations on digital images. Generally, digital image processing requires the use of complex algorithms, and hence, can be more sophisticated from a performance perspective at doing simple tasks. Many applications exist for digital image processing, one of which is Digital Image Transformation. Basically, Digital Image Transformation or DIT is an algorithmic and mathematical function that converts one set of digital objects into another set after performing some

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Grimes, David B., and Rajesh P. N. Rao. "Bilinear Sparse Coding for Invariant Vision." Neural Computation 17, no. 1 (2005): 47–73. http://dx.doi.org/10.1162/0899766052530893.

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Recent algorithms for sparse coding and independent component analysis (ICA) have demonstrated how localized features can be learned from natural images. However, these approaches do not take image transformations into account. We describe an unsupervised algorithm for learning both localized features and their transformations directly from images using a sparse bilinear generative model. We show that from an arbitrary set of natural images, the algorithm produces oriented basis filters that can simultaneously represent features in an image and their transformations. The learned generative mod

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Mann Parminder Singh, Navjot. "Medial Axis Transformation based Skeletonzation of Image Patterns using Image Processing Techniques." International Journal of Science and Research (IJSR) 1, no. 3 (2012): 220–23. http://dx.doi.org/10.21275/ijsr12120344.

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Бродская, Юлия Алексеевна, and Светлана Ивановна Яковлева. "KONIGSBERG-KALININGRAD IMAGE TRANSFORMATION." Вестник Тверского государственного университета. Серия: География и геоэкология, no. 1(33) (March 23, 2021): 82–92. http://dx.doi.org/10.26456/2226-7719-2021-1-82-92.

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Цель исследования - анализ трансформации городского образа на примере Кёнигсберга-Калининграда. Новизна исследования - в применение градостроительной схемы К.Линча (1960) к анализу разновременной пространственной структуры крупного старого немецкого города Кёнигсберга и послевоенного (современного) Калининграда. The aim of the research is to analyze the transformation of the urban image on the example of Königsberg-Kaliningrad. The novelty of the research lies in the application of the urban planning scheme of K. Linch (1960) to the analysis of the multi-temporal spatial structure of the large

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Sánchez-Morales, Maria-Eugenia, José-Trinidad Guillen-Bonilla, Héctor Guillen-Bonilla, Alex Guillen-Bonilla, Jorge Aguilar-Santiago, and Maricela Jiménez-Rodríguez. "Vectorial Image Representation for Image Classification." Journal of Imaging 10, no. 2 (2024): 48. http://dx.doi.org/10.3390/jimaging10020048.

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This paper proposes the transformation S→C→, where S is a digital gray-level image and C→ is a vector expressed through the textural space. The proposed transformation is denominated Vectorial Image Representation on the Texture Space (VIR-TS), given that the digital image S is represented by the textural vector C→. This vector C→ contains all of the local texture characteristics in the image of interest, and the texture unit T→ entertains a vectorial character, since it is defined through the resolution of a homogeneous equation system. For the application of this transformation, a new classi

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Slobodyanyuk, N. L. "ANNA AKHMATOVA’S CYBER IMAGE IN THE PERCEPTION OF THE MODERN READER." Vestnik of the Kyrgyz-Russian Slavic University 25, no. 2 (2025): 151–58. https://doi.org/10.36979/1694-500x-2025-25-2-151-158.

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The article considers the factors of transformation of the regularities of functioning of information and communication space of modern society and their reflection in the modern literary process, fixation of changes in the content of culture in media art texts in the digital space The phenomena of traditional culture, appearing in a new, digital context, undergo significant transformations. The projections of both cultural constructs and cultural environment into cyberspace, where they take on the character of content not limited by a fixed form, are studied. The object of the study is the im

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Foroughi Sabzevar, Mohsen, Masoud Gheisari, and James Lo. "Development and Assessment of a Sensor-Based Orientation and Positioning Approach for Decreasing Variation in Camera Viewpoints and Image Transformations at Construction Sites." Applied Sciences 10, no. 7 (2020): 2305. http://dx.doi.org/10.3390/app10072305.

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Image matching techniques offer valuable opportunities for the construction industry. Image matching, a fundamental process in computer vision, is required for different purposes such as object and scene recognition, video data mining, reconstruction of three-dimensional (3D) objects, etc. During the image matching process, two images that are randomly (i.e., from different position and orientation) captured from a scene are compared using image matching algorithms in order to identify their similarity. However, this process is very complex and error prone, because pictures that are randomly c

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Wang, Hexiang, Fengqi Liu, Qianyu Zhou, Ran Yi, Xin Tan, and Lizhuang Ma. "Continuous Piecewise-Affine Based Motion Model for Image Animation." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 6 (2024): 5427–35. http://dx.doi.org/10.1609/aaai.v38i6.28351.

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Image animation aims to bring static images to life according to driving videos and create engaging visual content that can be used for various purposes such as animation, entertainment, and education. Recent unsupervised methods utilize affine and thin-plate spline transformations based on keypoints to transfer the motion in driving frames to the source image. However, limited by the expressive power of the transformations used, these methods always produce poor results when the gap between the motion in the driving frame and the source image is large. To address this issue, we propose to mod

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Kalthom Adam H. Ibrahim, Mohammed Abdallah Almaleeh, Moaawia Mohamed Ahmed, and Dalia Mahmoud Adam. "Images Processing for Segmentation Neisseria Bacteria Cells." World Journal of Advanced Research and Reviews 12, no. 3 (2021): 573–79. http://dx.doi.org/10.30574/wjarr.2021.12.3.0672.

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This paper introduces the segmentation of Neisseria bacterial meningitis images. Images segmentation is an operation of identifying the homogeneous location in a digital image. The basic idea behind segmentation called thresholding, which be classified as single thresholding and multiple thresholding. To perform images segmentation, transformations and morphological operations processes are used to segment the images, as well as image transformation an edge detecting, filling operation, design structure element, and arithmetic operations technique is used to implement images segmentation. The

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