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Radiology, 1980
The enhancement of radiographic and fluoroscopic images using simple video analog techniques is described. In each instance, both the degree of enhancement and the features of the image to be enhanced are under the direct control of the radiologist. Noise is suppressed with a sharp cut-off, low-pass filter. Three types of analog circuits are discussed.
Norman A. Baily, R. J. Nachazel
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The enhancement of radiographic and fluoroscopic images using simple video analog techniques is described. In each instance, both the degree of enhancement and the features of the image to be enhanced are under the direct control of the radiologist. Noise is suppressed with a sharp cut-off, low-pass filter. Three types of analog circuits are discussed.
Norman A. Baily, R. J. Nachazel
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DSLR: Deep Stacked Laplacian Restorer for Low-Light Image Enhancement
IEEE transactions on multimedia, 2021Various images captured in complicated lighting conditions often suffer from deterioration of the image quality. Such poor quality not only dissatisfies the user expectation but also may lead to a significant performance drop in many applications.
Seokjae Lim, Wonjun Kim
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TBEFN: A Two-Branch Exposure-Fusion Network for Low-Light Image Enhancement
IEEE transactions on multimedia, 2021Images obtained under low-light conditions are usually accompanied by varied and highly unpredictable degradation. The uncertainty of the imaging environment makes the enhancement even more challenging.
K. Lu, Lihong Zhang
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Optical Society of America Annual Meeting, 1991
Blockwise transform image enhancement techniques are discussed. Previously, transform image enhancement has usually been based on the discrete Fourier transform (DFT) applied to the whole image. Two major drawbacks with the DFT are high complexity of implementation involving complex multiplications and additions, with intermediate results being complex
Sabzali Aghagolzadeh, Okan K. Ersoy
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Blockwise transform image enhancement techniques are discussed. Previously, transform image enhancement has usually been based on the discrete Fourier transform (DFT) applied to the whole image. Two major drawbacks with the DFT are high complexity of implementation involving complex multiplications and additions, with intermediate results being complex
Sabzali Aghagolzadeh, Okan K. Ersoy
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Image detection and enhancement
Applied Optics, 1981An optimal filtering approach is taken to the problem of detecting and enhancing a photographic image immersed in background or noise. The minimum mean square error criterion is shown to be not relevant to the optical employment of the Wiener filter.
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IEEE Transactions on Image Processing, 2001
Peer group image processing identifies a "peer group" for each pixel and then replaces the pixel intensity with the average over the peer group. Two parameters provide direct control over which image features are selectively enhanced: area (number of pixels in the feature) and window diameter (window size needed to enclose the feature). A discussion is
Yining Deng +3 more
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Peer group image processing identifies a "peer group" for each pixel and then replaces the pixel intensity with the average over the peer group. Two parameters provide direct control over which image features are selectively enhanced: area (number of pixels in the feature) and window diameter (window size needed to enclose the feature). A discussion is
Yining Deng +3 more
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Low-Light Image Enhancement With Semi-Decoupled Decomposition
IEEE transactions on multimedia, 2020Low-light image enhancement is important for high-quality image display and other visual applications. However, it is a challenging task as the enhancement is expected to improve the visibility of an image while keeping its visual naturalness.
Shijie Hao +4 more
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Local enhancement of compressed images
Journal of Mathematical Imaging and Vision, 1993zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Terrance L. Huntsberger +2 more
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Enhanced Visualization of Hyperspectral Images
IEEE Geoscience and Remote Sensing Letters, 2010An enhanced visualization algorithm for hyperspectral images (HSI) is presented in this paper. The visualization is based on the projection onto color matching functions of the human vision system. A contrast enhancement procedure is introduced making use of multiband gradient information.
Mahmood, Zahid, Scheunders, Paul
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Hierarchic recursive image enhancement
IEEE Transactions on Circuits and Systems, 1977The problem that is solved in this paper can be formulated as: given an observation of an image against the background of additive noise and given the statistics of the image and the noise, find an optimal estimate of the image such that the computer-time and storage requirements of the estimator are modest for images of, say 250 \times 250 points or ...
F. Schoute, M.t. Horst, Jan C. Willems
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