6,575 research outputs found

    Loop filtering and post-filtering for low-bit-rates moving picture coding

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    When an image is highly compressed by using the current coding standards, the decompressed image has noticeable image degradations such as blocking artifacts near the block boundaries, corner outliers at cross points of blocks and ringing noise near image edges. These image degradations are caused by quantization process of the 8 x 8 DCT coefficients. In order to restore the decompressed image, a loop-filtering algorithm and a post-filtering algorithm have been developed. The developed methods perform an adaptive filtering on the decompressed image according to blocking and ringing flags that are defined to reduce computation complexity. Performances of both algorithms are compared with respect to the image quality and the computation complexity. The comparison results show that the post-filtering is slightly better than or similar to the loop filtering with respect to peak signal-to-noise ratio (PSNR), whereas the subjective image qualities of both methods are quite similar. However, the computation complexity of the loop filtering is much less than that of the post-filtering. (C) 2001 Elsevier Science B.V. All rights reserved

    A postprocessing method for reducing quantization effects in low bit-rate moving picture coding

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    The reconstructed images from highly compressed MPEG data have noticeable image degradations, such as blocking artifacts near the block boundaries, corner outliers at crosspoints of blocks, and ringing noise near image edges because the MPEG quantizes the transformed coefficients of 8 x 8 pixel blocks. A postprocessing algorithm is proposed to reduce quantization effects, such as blocking artifacts, corner outliers, and ringing noise, in MPEG-decompressed images. The proposed postprocessing algorithm reduces the quantization effects adaptively by using both spatial frequency and temporal information extracted from the compressed data. The blocking artifacts are reduced by one-dimensional (1-D) horizontal and vertical low-pass filtering (LPF), and the ringing noise is reduced by two-dimensional (2-D) signal-adaptive filtering (SAF). A comparison study of the peak signal-to-noise ratio (PSNR) and the computation complexity analysis between the proposed algorithm and the MPEG-4 VM (verification model) postprocessing algorithm is performed by computer simulation with several image sequences. According to the comparison study of PSNR and computation complexity analysis, the proposed algorithm shows better performance than the VM postprocessing algorithm, whereas the subjective image qualities of both algorithms are similar
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