&lt;title&gt;Multiresolutional encoding and decoding in embedded image and video coders&lt;/title&gt;

Xiong, Zixiang; Kim, Beong-Jo; Pearlman, William A.

doi:10.1117/12.316548

Cited by 4 publications

(8 citation statements)

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“…Figures 3 (a) and (b) show the layered bit streams generated by the previous multiresolutional encoding [2] and the proposed multiresolutional encoding at 1 bpp and 0.1 bpp, respectively. In the figures, we can see that the first layer of the bit stream generated by the previous multiresolutional encoding method is much longer than the first layer of our algorithm.…”

Section: Experiments Resultsmentioning

confidence: 99%

“…In the previous work [2], they decoded the whole bit stream and selected the necessary coefficients to reconstruct an image they wanted. It is difficult to use this function in the narrow bandwidth environment because the whole bit stream should be transmitted to reconstruct even a small image.…”

Section: Multiresolutional Codingmentioning

confidence: 99%

“…It would be desirable to incorporate such a feature into an image coding system without incurring heavy cost such as increased computational complexity or reduced rate-distortion performance. Xiong et al proposed a multiresolutioal image decoding method [2]. They selected necessary coefficients to reconstruct various resolution images.…”

Section: Introductionmentioning

confidence: 99%

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A Multiresolutionnal Coding Method Based on SPIHT

Park

Lee²,

Park³

2001

Advances in Multimedia Information Processing — PCM 2001

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Abstract. In this work, we incorporate a multiresolutional coding functionality into the SPIHT algorithm [1]. The multiresolutional coding can be considered as a kind of the region of interest (ROI) coding with multiple regions of interest. Therefore, the ROI coding proposed by authors can be extended for the multiresolutional functionality without any cost in performance. The parent of ROI (PROI) and the multiple lists for insignificant sets and pixels, which were proposed for the ROI coding, are also used for the multiresolution coding.

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Section: Experiments Resultsmentioning

confidence: 99%

Section: Multiresolutional Codingmentioning

confidence: 99%

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A Multiresolutionnal Coding Method Based on SPIHT

Park

Lee²,

Park³

2001

Advances in Multimedia Information Processing — PCM 2001

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“…By reordering the transmitted bit stream, the SPIHT algorithm can be made spatially scalable [18], [29]. Compared against SPIHT without arithmetic coding, the spatially scalable SPIHT has no loss in performance (PSNR versus bit rate at the final full size) and retains some progressivity.…”

Section: Multiresolution Codersmentioning

confidence: 99%

Image quality evaluation based on recognition times for fast image browsing applications

Schilling

Cosman

2002

IEEE Trans. Multimedia

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Mean squared error (mse) and peak signal-tonoise-ratio (PSNR) are the most common methods for measuring the quality of compressed images, despite the fact that their inadequacies have long been recognized. Quality for compressed still images is sometimes evaluated using human observers who provide subjective ratings of the images. Both SNR and subjective quality judgments, however, may be inappropriate for evaluating progressive compression methods which are to be used for fast browsing applications. In this paper, we present a novel experimental and statistical framework for comparing progressive coders. The comparisons use response time studies in which human observers view a series of progressive transmissions, and respond to questions about the images as they become recognizable. We describe the framework and use it to compare several well-known algorithms [JPEG, set partitioning in hierarchical trees (SPIHT), and embedded zerotree wavelet (EZW)], and to show that a multiresolution decoding is recognized faster than a single large-scale decoding. Our experiments also show that, for the particular algorithms used, at the same PSNR, global blurriness slows down recognition more than do localized "splotch" artifacts.

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“…In [30], the resolution and frame rate scalability is obtained by partitioning and/or reordering the bit stream from the 3-D SPIHT. A comprehensive version of the 3-D SPIHT is presented in [14].…”

Section: Introductionmentioning

confidence: 99%

Optimal 3-d coefficient tree structure for 3-d wavelet video coding

Dong

Zheng

et al. 2003

IEEE Trans. Circuits Syst. Video Technol.

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An optimal three-dimensional (3-D) coefficient tree structure for 3-D zerotree wavelet video coding is considered in this paper. The 3-D zerotree wavelet video coding is inspired by the success of the two-dimensional (2-D) zerotree wavelet image coding. Existing 3-D zerotree wavelet video codecs use the either symmetric or symmetric-alike 3-D tree structure, which is a straightforward extension of the symmetric 2-D tree structure in the zerotree wavelet image coding. In this paper, we show that the 3-D zerotree coding does not need to be applied symmetrically along all the directions, as the 2-D zerotree image coding does. We find that an asymmetric 3-D tree structure working with a more flexible asymmetric 3-D wavelet transform can produce a higher compression ratio than traditional symmetric approaches. The new 3-D tree structure can be used to improve the rate-distortion performance of many existing 3-D zerotree wavelet video codecs without sacrificing other features such as scalability and computational efficiency. The new tree structure is applied to the 3-D set partitioning in hierarchical trees method and receives convincing peak signal-to-noise ratio improvements in experiments. Index Terms-Set partitioning in hierarchical trees (SPIHT), symmetric and symmetric-alike three-dimensional (3-D) tree structure, 3-D zerotree coding, video compression, wavelet transform.

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<title>Multiresolutional encoding and decoding in embedded image and video coders</title>

Cited by 4 publications

References 0 publications

A Multiresolutionnal Coding Method Based on SPIHT

A Multiresolutionnal Coding Method Based on SPIHT

Image quality evaluation based on recognition times for fast image browsing applications

Optimal 3-d coefficient tree structure for 3-d wavelet video coding

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