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Relevant bibliographies by topics / Gray scale interframe interpolation

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Academic literature on the topic 'Gray scale interframe interpolation'

Author: Grafiati

Published: 3 June 2025

Last updated: 23 June 2025

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Journal articles on the topic "Gray scale interframe interpolation"

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Zhang, Lu Ping, Biao Li, and Lu Ping Wang. "A Infrared Small Moving Object Extraction Method in the Context of Complex Background Motion." Advanced Materials Research 760-762 (September 2013): 1879–83. http://dx.doi.org/10.4028/www.scientific.net/amr.760-762.1879.

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The detection of small moving target in the context of complex background is a difficult issue. A method combining interframe differential registration and adaptive wiener filtering aimed to suppress background to detect moving object in complex background is proposed. The fixed background in the fore-and-aft frames can be filtered out by the interframe registration which preserves the moving target, parts of background and noise due to interframe movement and the gray-scale fluctuation. On one hand the complex background is estimated by an adaptive wiener filter, and the background suppression leaves the high-frequency regions containing the moving target in image. On the other hand, most of the high-frequency regions corresponding to non-target area are eliminated by the inter-frame registration in the differential images. The motion of target is continual in image sequences, while the position of the leaked background is relatively fixed and the noise is of small size. The fusion of the background suppression and inter-frame registration makes the discrimination of targets, background and noise possible. The small moving target is detected by trajectory association based on its interframe trajectory continuity. Experiment results verify the feasibility of the method.

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Higgins, W. E., C. J. Orlick, and B. E. Ledell. "Nonlinear filtering approach to 3-D gray-scale image interpolation." IEEE Transactions on Medical Imaging 15, no. 4 (1996): 580–87. http://dx.doi.org/10.1109/42.511761.

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Kim, Sang-Yup, and Seong-Whan Lee. "Gray-Scale Nonlinear Shape Normalization Method for Handwritten Oriental Character Recognition." International Journal of Pattern Recognition and Artificial Intelligence 12, no. 01 (1998): 81–95. http://dx.doi.org/10.1142/s0218001498000075.

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In general, nonlinear shape normalization methods for binary images have been used in order to compensate for the shape distortions of handwritten characters. However, in most document image analysis and recognition systems, a gray-scale image is first captured and digitized using a scanner or a video camera, then a binary image is extracted from the original gray-scale image using a certain extraction technique. This binarization process may remove some useful information of character images such as topological features, and introduce noises to character background. These errors are accumulated in nonlinear shape normalization step and transferred to the following feature extraction or recognition step. They may eventually cause incorrect recognition results. In this paper, we propose nonlinear shape normalization methods for gray-scale handwritten Oriental characters in order to minimize the loss of information caused by binarization and compensate for the shape distortions of characters. Two-dimensional linear interpolation technique has been extended to nonlinear space and the extended interpolation technique has been adopted in the proposed methods to enhance the quality of normalized images. In order to verify the efficiency of the proposed methods, the recognition rate, the processing time and the computational complexity of the proposed algorithms have been considered. The experimental results demonstrate that the proposed methods are efficient not only to compensate for the shape distortions of handwritten Oriental characters but also to maintain the information in gray-scale Oriental characters.

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Scollar, Irwin, Bernd Weidner, and Karel Segeth. "Display of archaeological magnetic data." GEOPHYSICS 51, no. 3 (1986): 623–33. http://dx.doi.org/10.1190/1.1442116.

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Magnetic data from archaeological sites have traditionally been displayed by contour, isometric, and dot‐density plotting, or by simulated gray‐scale techniques using symbol overprinting. These methods do not show fine linear structures in the data which are of great interest to archaeologists. If true gray‐scale methods using a modern video display, followed by film recording for hard copy are employed, image processing techniques can be applied to enhance the geometric structures of archaeological interest. Interpolation techniques for enlarging data to full screen size, along with compression methods to keep data within gray‐scale capabilities, are needed. Such techniques would introduce minimum distortion and allow faint details to be seen in the vicinity of strong anomalies. Postprocessing methods based on rapid image spatial filtering and enhancement algorithms could then be applied in an interactive environment.

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Wang, Zhen-xin, and Ji-hong Ouyang. "Curve length estimation based on cubic spline interpolation in gray-scale images." Journal of Zhejiang University SCIENCE C 14, no. 10 (2013): 777–84. http://dx.doi.org/10.1631/jzus.c1300056.

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Richard, William D., and R. Martin Arthur. "Real-Time Ultrasonic Scan Conversion via Linear Interpolation of Oversampled Vectors." Ultrasonic Imaging 16, no. 2 (1994): 109–23. http://dx.doi.org/10.1177/016173469401600204.

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Scan conversion is required in order to display conventional B-mode ultrasonic signals, which are acquired along radii at varying angles, on standard Cartesian-coordinate video monitors. For real-time implementations, either nearest-neighbor or bilinear interpolation is usually used in scan conversion. If the sampling rate along each radius is high enough, however, the gray-scale value of a given pixel can be interpolated accurately using the nearest samples on two adjacent vectors. The required interpolation then reduces to linear interpolation. Oversampling by a factor of 2 along with linear interpolation was superior to bilinear interpolation of vectors sampled to match pixel-to-pixel spacing in 6 representative B-mode images. A novel 8-bit linear interpolation algorithm was implemented as a CMOS VLSI circuit using a readily available, high-level synthesis tool. The circuit performed 30 million interpolations per second. Arithmetic results produced by the 8-bit interpolator on 7-bit samples were virtually identical to IEEE-format, single-precision, floating-point results.

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Xu, Guang Shen, and Gen Yang. "Distortion Correction of Image in Integral Stereolithography System." Applied Mechanics and Materials 63-64 (June 2011): 197–200. http://dx.doi.org/10.4028/www.scientific.net/amm.63-64.197.

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There is geometric distortion of image in integral Stereolithography (SL) system, and the geometric distortion will influence the building accuracy of the SL system. To improve the building accuracy of the SL system, researches of distortion correction of image in the SL system are carried out. The distortion model of binary cubic polynomial interpolation is established with least-square method. The gray scale rebuilding is implemented with space-variable linear interpolation by using VC++6.0. The experimental results indicate that the geometric distortion of the image in integral SL system has been eliminated remarkably, and the radial RMS error is 0.96 pixels. The research lays a foundation for improving building accuracy of the integral SL System.

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Cruz-Bernal, Alejandra, Martha M. Flores-Barranco, Dora L. Almanza-Ojeda, Sergio Ledesma, and Mario A. Ibarra-Manzano. "Analysis of the Cluster Prominence Feature for Detecting Calcifications in Mammograms." Journal of Healthcare Engineering 2018 (December 30, 2018): 1–11. http://dx.doi.org/10.1155/2018/2849567.

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In mammograms, a calcification is represented as small but brilliant white region of the digital image. Earlier detection of malignant calcifications in patients provides high expectation of surviving to this disease. Nevertheless, white regions are difficult to see by visual inspection because a mammogram is a gray-scale image of the breast. To help radiologists in detecting abnormal calcification, computer-inspection methods of mammograms have been proposed; however, it remains an open important issue. In this context, we propose a strategy for detecting calcifications in mammograms based on the analysis of the cluster prominence (cp) feature histogram. The highest frequencies of the cp histogram describe the calcifications on the mammography. Therefore, we obtain a function that models the behaviour of the cp histogram using the Vandermonde interpolation twice. The first interpolation yields a global representation, and the second models the highest frequencies of the histogram. A weak classifier is used for obtaining a final classification of the mammography, that is, with or without calcifications. Experimental results are compared with real DICOM images and their corresponding diagnosis provided by expert radiologists, showing that the cp feature is highly discriminative.

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Wang, Jang Ping, Guo Ming Huang, and Sheng Hua Yurs. "Profiles Detection in Ring Convex Forming by ACLN with Sub-Pixel Accuracy." Key Engineering Materials 364-366 (December 2007): 199–204. http://dx.doi.org/10.4028/www.scientific.net/kem.364-366.199.

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An optical measuring system for the ring test is proposed. In this approach, the machine vision inspection equipment is first built to record and capture the images of ring test from the digital camcorder.The image processing procedures to detect and locate the edge points of the inner and outer radii in ring convex forming are presented. Unlike the conventional sub-pixel estimation based on gray-level values, the quantity (8 bits) of color’s scale has been adopted. In image processing procedures, a clustering method called Adaptive Competitive Learning Network (ACLN) is first used to classify the image hues which represent the different heights of bulge profiles on the top of ring, and then the edge points can be searched by the interpolation step of subpixel accuracy. The calibration curves constructed by the mode of non-constant friction factor called F-value approach is designed to compare and check with the measurement data. The experimental results will be presented and discussed in this study.

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Sonehara, Noboru. "Special Issue Imaging Processing-Algorithm and System. Multi-level Representation and Intensity-level Interpolation of a Gray Scale Image by Relaxation Nueral Network Models." Journal of the Institute of Television Engineers of Japan 45, no. 10 (1991): 1190–98. http://dx.doi.org/10.3169/itej1978.45.1190.

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Book chapters on the topic "Gray scale interframe interpolation"

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Tóth, Márton József, and Balázs Csébfalvi. "Distribution Interpolation of the Radon Transforms for Shape Transformation of Gray-Scale Images and Volumes." In Communications in Computer and Information Science. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25117-2_2.

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Conference papers on the topic "Gray scale interframe interpolation"

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Stringham, Russell R., and William A. Barrett. "Shape-based interpolation of gray-scale serial slice images." In Medical Imaging 1993, edited by Murray H. Loew. SPIE, 1993. http://dx.doi.org/10.1117/12.154495.

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Yang, Wenping, Hao Meng, Jihua Fu, and Zhongyu Wang. "Subpixel location method of Bessel light center based on improved spin filtering and gray scale interpolation." In Seventh International Symposium on Instrumentation and Control Technology, edited by Jiancheng Fang and Zhongyu Wang. SPIE, 2008. http://dx.doi.org/10.1117/12.807375.

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Tong, Xianqiao, Tomonari Furukawa, and Saied Taheri. "Speed Enhancement of Displacement and Strain Field Measurement Using Graphics Processing Unit." In ASME 2012 Rail Transportation Division Fall Technical Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/rtdf2012-9413.

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This paper presents the speed enhancement of displacement and strain field measurement using graphics processing unit (GPU) towards real-time field measurement. The displacement and strain field measurement technique to be enhanced is a vision-based dot centroid tracking (DCT) method which measures the darkness of each pixel in gray scale, identifies dots marked on a specimen, derives dot centroids using pixel darkness information and derives displacement and strain fields by tracking the centroids and deriving and interpolating the nodal displacements and strains. The proposed enhancement begins by finding parallel processes in both the image analysis phase and the field estimation phase. The centroid derivation and tracking of marked dots in the image analysis phase are computed independently for each marked dot whereas the derivation, interpolation and estimation of the displacement and strain field are computed parallel as well with respect to the interpolated points which covers the evaluated field. The proposed enhancement then accelerates the displacement and strain field estimation by storing the pixel and dot information as a predefined index look-up table and a new measurement in a shared buffer in the GPU’s shared memory. The use of the shared buffer with a look-up table avoids the duplicated memory allocation and contributes to not only speed but also memory usage. Numerical examples have first investigated the validity and performance of the proposed enhancement through parametric studies. A comparison with field measurement using only a central processing unit (CPU) shows that the proposed enhancement gains at least 10 times speedup when the same accuracy is attained. The proposed approach was then applied to the displacement and strain field measurement of a rail in a three-point bending test under relatively fast periodic loadings, and its ability to capture real-time behavior has been demonstrated.

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