An effective compression artifacts removal algorithm is proposed based on the theory of projections onto convex sets (POCS). It includes a block classification procedure, a ringing detection procedure, prediction of the spatial distribution of the quantization errors and estimation of the visibility of the compression artifacts. Information gained from both the spatial and transform domains, is incorporated into adaptive projections. Experiments performed on JPEG-compressed images, demonstrate the effectiveness of the proposed algorithm in suppressing both blocking and ringing artifacts, as well as the ability of the algorithm to preserve the image sharpness.
A real time algorithm for fusion of differently exposed images is proposed in this paper. The algorithm blends the details from two images of high dynamic range scene, acquired with different exposure values, into one output image which can be displayed on low dynamic range devices. The blending is performed in the spatial domain, using pixel by pixel approach, thus eliminating the need for expensive block processing or transform domain coding. The proposed scheme works both on grey and color images. The algorithm shows high efficiency, which make it applicable on low processing power platforms, such as mobile devices. The obtained results are visually comparable with previously published algorithms that are computationally much more expensive.
A new method to reduce the severity ofblocking artifacts in block DCT-based compressed images and video streams is presented in this paper. The proposed algorithm works in three steps. measurement of the visibility of the artifacts, edge detection, and adaptive processing ofthe degraded image. Thefirst step is performed in the DCT domain, while steps two and three are performed in the spatial domain. The algorithm 'sperformance is tested experimentally.
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