Results 201 to 210 of about 10,626 (257)
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Image sharpening by morphological filtering
Pattern Recognition, 2000This paper introduces a class of iterative morphological image operators with applications to sharpen digitized gray-scale images. It is proved that all image operators using a concave structuring function have sharpening properties. By using a Laplacian property, we introduce the underlying partial differential equation that governs this class of ...
M J T Reinders
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Image sharpening in the JPEG domain
IEEE Transactions on Image Processing, 1999We present a new technique for sharpening compressed images in the discrete-cosine-transform domain. For images compressed using the JPEG standard, image sharpening is achieved by suitably scaling each element of the encoding quantization table to enhance the high-frequency characteristics of the image.
V Bhaskaran, K Konstantinides
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Heaviside image edge sharpening
2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP), 2015In this paper, we propose an automatic and efficient method to enhance edge sharpness of images. Starting from an image with blur edges, we improve the edges using transformed Heaviside functions for better visualization. In addition, we provide an efficient method to directly compute the scaling and shifting factors of the transformed Heaviside ...
Liang-Jian Deng +3 more
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Statistics for image sharpening
Statistica Neerlandica, 2007Sharpening filters increase the depth of digital images by adding a fraction of their gradient. This portion is tuned by a coefficient which is usually selected according to rules of thumb or subjective evaluation. This paper proposes statistical measures for designing such a parameter in a nearly automatic way, avoiding subjective evaluations.
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Image Sharpening with Optimized PSNR
2019 IEEE International Conference on Signal and Image Processing Applications (ICSIPA), 2019A family of matrix filters are introduced through approximations to directional digital derivatives. Images can be sharpened by combining all the eight directional filtered images together. The two parameters in the filter family are determined by desired PSNR so that a given image is sharpened with optimized PSNR.
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Optimizing Image Sharpening Algorithm on GPU
2015 44th International Conference on Parallel Processing, 2015Sharpness is an algorithm used to sharpen images. As the increase of image size, resolution, and the requirements for real-time processing, the performance of sharpness needs to get improved greatly. The independent pixel calculation of sharpness makes a good opportunity to use GPU to largely accelerate the performance. However, to transplant it to GPU,
Mengran Fan +4 more
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Colour Constant Image Sharpening
2010 20th International Conference on Pattern Recognition, 2010In this paper, we introduce a new sharpening method which guarantees colour constancy and resolves the problem of equiluminance colours. The algorithm is similar to unsharp masking in that the gradients are calculated at different scales by blurring the original with a variable size kernel.
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Anisotropic color image denoising and sharpening
2014 IEEE International Conference on Image Processing (ICIP), 2014In this paper, a new model for color image enhancement based on diffusion-shock filter coupling is presented. The proposed method is based on the consideration of single vectors of the gradient magnitude and the second derivatives as a manner to relate the processing of the different color components of the image. This solution avoids the apparition of
Salim Bettahar +2 more
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A Wavelet Based Image Sharpening Algorithm
2008 International Conference on Computer Science and Software Engineering, 2008The fundamental idea of image sharpening is to add to the input signal a high-pass filtered version of the signal itself. Wavelet coefficients provide multiresolution high frequency components of an image. Making use of this property, in this paper, we propose a wavelet-based algorithm for image sharpening.
Liu Ying, Ng Tek Ming, Liew Beng Keat
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Fuzzy Image Sharpening of Historical Prints
2006 IEEE International Conference on Fuzzy Systems, 2006Established methods for sharpening details in images often lead to the magnification of background noise at the expense of detail clarity. This paper applies a method of image sharpening based on fuzzy morphology which is used to enhance historical images.
Michael A. Wirth, Dennis Nikitenko
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