Soft Compression for Lossless Image Coding Based on Shape Recognition
Soft compression is a lossless image compression method that is committed to eliminating coding redundancy and spatial redundancy simultaneously. To do so, it adopts shapes to encode an image. In this paper, we propose a compressible indicator function with regard to images, which gives a threshold...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-12-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/23/12/1680 |
| _version_ | 1797504944800006144 |
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| author | Gangtao Xin Pingyi Fan |
| author_facet | Gangtao Xin Pingyi Fan |
| author_sort | Gangtao Xin |
| collection | DOAJ |
| description | Soft compression is a lossless image compression method that is committed to eliminating coding redundancy and spatial redundancy simultaneously. To do so, it adopts shapes to encode an image. In this paper, we propose a compressible indicator function with regard to images, which gives a threshold of the average number of bits required to represent a location and can be used for illustrating the working principle. We investigate and analyze soft compression for binary image, gray image and multi-component image with specific algorithms and compressible indicator value. In terms of compression ratio, the soft compression algorithm outperforms the popular classical standards PNG and JPEG2000 in lossless image compression. It is expected that the bandwidth and storage space needed when transmitting and storing the same kind of images (such as medical images) can be greatly reduced with applying soft compression. |
| first_indexed | 2024-03-10T04:11:37Z |
| format | Article |
| id | doaj.art-e8e44cf074774a03b5bf9d8668863507 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-10T04:11:37Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-e8e44cf074774a03b5bf9d86688635072023-11-23T08:11:35ZengMDPI AGEntropy1099-43002021-12-012312168010.3390/e23121680Soft Compression for Lossless Image Coding Based on Shape RecognitionGangtao Xin0Pingyi Fan1Department of Electronic Engineering, Tsinghua University, Beijing 100084, ChinaDepartment of Electronic Engineering, Tsinghua University, Beijing 100084, ChinaSoft compression is a lossless image compression method that is committed to eliminating coding redundancy and spatial redundancy simultaneously. To do so, it adopts shapes to encode an image. In this paper, we propose a compressible indicator function with regard to images, which gives a threshold of the average number of bits required to represent a location and can be used for illustrating the working principle. We investigate and analyze soft compression for binary image, gray image and multi-component image with specific algorithms and compressible indicator value. In terms of compression ratio, the soft compression algorithm outperforms the popular classical standards PNG and JPEG2000 in lossless image compression. It is expected that the bandwidth and storage space needed when transmitting and storing the same kind of images (such as medical images) can be greatly reduced with applying soft compression.https://www.mdpi.com/1099-4300/23/12/1680lossless image compressioninformation theorystatistical distributionscompressible indicator functionimage set compression |
| spellingShingle | Gangtao Xin Pingyi Fan Soft Compression for Lossless Image Coding Based on Shape Recognition Entropy lossless image compression information theory statistical distributions compressible indicator function image set compression |
| title | Soft Compression for Lossless Image Coding Based on Shape Recognition |
| title_full | Soft Compression for Lossless Image Coding Based on Shape Recognition |
| title_fullStr | Soft Compression for Lossless Image Coding Based on Shape Recognition |
| title_full_unstemmed | Soft Compression for Lossless Image Coding Based on Shape Recognition |
| title_short | Soft Compression for Lossless Image Coding Based on Shape Recognition |
| title_sort | soft compression for lossless image coding based on shape recognition |
| topic | lossless image compression information theory statistical distributions compressible indicator function image set compression |
| url | https://www.mdpi.com/1099-4300/23/12/1680 |
| work_keys_str_mv | AT gangtaoxin softcompressionforlosslessimagecodingbasedonshaperecognition AT pingyifan softcompressionforlosslessimagecodingbasedonshaperecognition |