Affiliated with RCfalse
Constrained quantization based transform domain down-conversion for image compression
Shuyuan Zhu1; Liaoyuan Zeng1; Bing Zeng1; Jiantao Zhou2
Conference NameIEEE International Symposium on Circuits and Systems (ISCAS)
Source PublicationProceedings - IEEE International Symposium on Circuits and Systems
Conference Date22-25 May 2016
Conference PlaceMontreal, QC, Canada

The image down-conversion may be used in the block-based image compression because it can help save lots of bit-counts for each individual block. A straightforward way to implement the transform domain down-conversion is to truncate some high-frequency components to get a down-sized coefficient block. However, directly using this down-sized coefficient block to reconstruct a completed image block will lead to a serious quality degradation. In this paper, we propose a constrained quantization based transform domain down-conversion (CQTDD) to help compress each 16×16 macro-block and it makes the coding quality of 1/4 selected pixels (according to a regular pattern) in each macro-block much higher than that can be achieved by using the traditional truncation based approach. Meanwhile, the other 3/4 pixels will be interpolated by using those 1/4 well-reconstructed pixels. Furthermore, these 1/4 pixels are optimized before the compression to help get a more efficient interpolation. Finally, the proposed CQTDD works with the JPEG baseline coding together as two candidate coding modes in our proposed compression scheme. Experimental results demonstrate that our proposed method may offer a remarkable quality gain, both objectively and subjectively, compared with some existing methods.

KeywordConstrained Quantization Down-conversion Image Compression
URLView the original
Indexed ByCPCI-S
WOS Research AreaEngineering
WOS SubjectEngineering, Electrical & Electronic
WOS IDWOS:000390094700209
Fulltext Access
Citation statistics
Cited Times [WOS]:1   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
Faculty of Science and Technology
Affiliation1.Institute of Image Processing University of Electronic Science and Technology of China, Chengdu, China
2.Faculty of Science and Technology University of Macau, Macau, China
Recommended Citation
GB/T 7714
Shuyuan Zhu,Liaoyuan Zeng,Bing Zeng,et al. Constrained quantization based transform domain down-conversion for image compression[C],2016:806-809.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Shuyuan Zhu]'s Articles
[Liaoyuan Zeng]'s Articles
[Bing Zeng]'s Articles
Baidu academic
Similar articles in Baidu academic
[Shuyuan Zhu]'s Articles
[Liaoyuan Zeng]'s Articles
[Bing Zeng]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Shuyuan Zhu]'s Articles
[Liaoyuan Zeng]'s Articles
[Bing Zeng]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.