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International Workshop on Advanced Imaging Technology (IWAIT)

作者： Ogawa, Kodai Kita, Yasuyo Matsuda, Ichiro Itoh, Susumu Kameda, Yusuke Tokyo Univ Sci Dept Elect Engn 2641 Yamazaki Noda Chiba 2788510 Japan Sophia Univ Tokyo Japan

ISBN: (数字)9781510653320

ISBN: (纸本)9781510653320;9781510653313

We previously proposed a method of designing a 2D FIR filter that can maximize the well-known objective quality index called SSIM. The designed filter can be used as a post processing tool for lossy image coding methods to reduce coding artifacts. In this scenario, there is a trade-off between the amount of side information on filter coefficients and the obtained gain in image quality. In this paper, effectiveness of the designed filters on the rate-SSIM based coding performance is evaluated under different settings of the size and quantization precision of the filter coefficients. Moreover, we introduce symmetric constraints on the filter coefficients to reduce the side information.

关键词： SSIM post filter coding artifacts reduction symmetric constraints on filter coefficients.

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2D Filter Design for coding artifacts reduction Using Structural Similarity as a Metric

2D Filter Design for Coding Artifacts Reduction Using Struct...

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International Workshop on Advanced Imaging Technology (IWAIT)

作者： Ogawa, Kodai Kameda, Yusuke Kita, Yasuyo Matsuda, Ichiro Itoh, Susumu Univ Tokyo Sci Fac Sci & Technol Dept Elect Engn 2641 Yamazaki Noda Chiba 2788510 Japan

ISBN: (数字)9781510643659

ISBN: (纸本)9781510643659

This paper describes a method of designing a 2D post filter for reducing coding artifacts caused by lossy image compression. Though Mean Squared Error (MSE) has been typically used in such filter design, it is not necessarily a good quality measure in terms of consistency with subjective perception. In this paper, we employ a more reliable quality measure called Structural SIMilarity (SSIM), and derive filter coefficients that can maximize the SSIM score for each image.

关键词： SSIM post filter coding artifacts reduction

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Simultaneous coding artifact reduction and sharpness enhancement for block-based compressed images and videos

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SIGNAL PROCESSING-IMAGE COMMUNICATION 2008年第6期23卷 463-470页

作者： Shao, Ling Philips Res Labs NL-5656 AE Eindhoven Netherlands

in this paper, an efficient least mean square (LMS) optimization algorithm based on the ordering of pixels is proposed for simultaneous sharpness enhancement and coding artifact reduction. The pixels in a filter aperture are ordered according to their spatial distances and intensity deviations to the central pixel. The optimized filter coefficients for the ordered pixels are obtained by training on a dataset that is composed of the original images and the compressed blurred versions of the original images. The pixel ordering procedure makes the algorithm more efficient for training and much cheaper in terms of classification than other LMS techniques. Experimental results show the superior performance of the proposed algorithm to the state-of-the-art classification-based techniques. (C) 2008 Elsevier B.V. All rights reserved.

关键词： coding artifacts reduction sharpness enhancement least mean square optimization adaptive filter classification

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coding Artifact reduction of JPEG Images Using SSIM-optimal Filtering with Quantization Constraint

Coding Artifact Reduction of JPEG Images Using SSIM-optimal ...

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International Workshop on Advanced Imaging Technology (IWAIT)

作者： Shigedomi, Yosuke Suzuki, Kaiyu Matsuda, Ichiro Tokyo Univ Sci Dept Elect Engn 2641 Yamazaki Noda Chiba 2788510 Japan

ISBN: (数字)9781510679931

ISBN: (纸本)9781510679931;9781510679924

Since the JPEG standard employs discrete cosine transform (DCT) based lossy coding algorithm, quality degradation due to coding artifacts is unavoidable especially at low coding rates. In order to alleviate this problem, we previously proposed a post filtering method that can maximize the well-known objective quality index called SSIM. In this paper, we combine the method with the projection onto convex sets (POCS) algorithm to exploit quantization constraint (QC) prior on DCT coefficients extracted from the JPEG image. Experimental results indicate that SSIM scores of the JPEG images are improved by applying the POCS algorithm.

关键词： SSIM post filter coding artifacts reduction quantization constraint projection onto convex sets

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Low Bit-Rates Image coding via Wavelet Domain Downsampling and Dual Wavelet-Pixel Domain Reconstruction 13

Low Bit-Rates Image Coding via Wavelet Domain Downsampling a...

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13th IEEE International Conference on Signal Processing (ICSP)

作者： He Xiaohai Chen Honggang Zhang Yijun Wu Xiaoqiang Sichuan Univ Coll Elect & Informat Engn Chengdu Sichuan Peoples R China

ISBN: (纸本)9781509013456

At low bit-rates, the conventional image coding standards, e.g., JPEG and JPEG 2000, do not have good compression performance due to the insufficiency of coding bits. A common solution to this problem is downsampling before encoding and reconstruction after decoding. Inspired by the wavelet domain downsampling-based compression scheme, we establish an enhanced low bit-rates coding framework by making the following improvements. Firstly, a regression priors-based coding artifacts reduction (RCAR) method is incorporated to preprocess the decoded low-resolution (LR) image;secondly, given the decoded low frequency wavelet coefficients, we propose to estimate its corresponding high frequency wavelet coefficients by using the joint optimized regressors (JOR) model to recover more information lost in downsampling phase;finally, the effective group-based sparse representation (GSR) model, which exploits both the nonlocal self-similarity and local sparsity properties, is utilized to perform soft decoding on the result of wavelet reconstruction. Experimental results suggest that the proposed framework outperforms JPEG 2000 at low to medium bit-rates in terms of both quantitative and visual comparisons.

关键词： Low bit-rates image coding wavelet downsampling coding artifacts reduction wavelet coefficients estimation group-based sparse representation

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Low Bit-Rates Image coding via Wavelet Domain Downsampling and Dual Wavelet-Pixel Domain Reconstruction

Low Bit-Rates Image Coding via Wavelet Domain Downsampling a...

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2016 IEEE 13th International Conference on Signal Processing（ICSP2016）

作者： He Xiaohai Chen Honggang Zhang Yijun Wu Xiaoqiang College of Electronics and Information Engineering Sichuan University

At low bit-rates, the conventional image coding standards, e.g., JPEG and JPEG 2000, do not have good compression performance due to the insufficiency of coding bits.A common solution to this problem is downsampling before encoding and reconstruction after decoding. Inspired by the wavelet domain downsampling-based compression scheme, we establish an enhanced low bit-rates coding framework by making the following improvements. Firstly, a regression priors-based coding artifacts reduction(RCAR) method is incorporated to preprocess the decoded low-resolution(LR) image;secondly,given the decoded low frequency wavelet coefficients, we propose to estimate its corresponding high frequency wavelet coefficients by using the joint optimized regressors(JOR) model to recover more information lost in downsampling phase;finally, the effective group-based sparse representation(GSR) model, which exploits both the nonlocal self-similarity and local sparsity properties, is utilized to perform soft decoding on the result of wavelet reconstruction. Experimental results suggest that the proposed framework outperforms JPEG 2000 at low to medium bit-rates in terms of both quantitative and visual comparisons.

关键词： Low bit-rates image coding wavelet downsampling coding artifacts reduction wavelet coefficients estimation groupbased sparse representation

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