47‐4: A Novel Demura Compensation Data Compression Algorithm based on JPEG‐LS
JPEG‐LS is a lossless/near‐lossless image compression algorithm based on context modeling, which has the advantages of easy implementation, low resource consumption and high compression rate. It is widely used in the compression field of continuous‐tone still images. However, single image compressio...
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| Veröffentlicht in: | SID International Symposium Digest of technical papers Jg. 55; H. 1; S. 634 - 637 |
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01.06.2024
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| Abstract | JPEG‐LS is a lossless/near‐lossless image compression algorithm based on context modeling, which has the advantages of easy implementation, low resource consumption and high compression rate. It is widely used in the compression field of continuous‐tone still images. However, single image compression has significant latency and high hardware resource consumption issues, as the JPEG‐LS algorithm requires pixel by pixel prediction and real‐time context updates during the compression process, which is not conducive to algorithm IP implementation. Based on Demura compensation data compression requirements, this article has made changes to the pixel prediction method of the JPEG‐LS algorithm and delayed the update of the context to solve the compression latency and resource consumption issues. After algorithm optimization (NJPEGLS), the linebuffer resource occupation was reduced by 8/9, the clock frequency reached above 140 MHz, and the comprehensive compression rate loss was within 4.5%, meeting the demand for Demura compensation data compression/decompression. In this paper, we also conducted statistics and analysis on the distribution of values, and found that the distribution of values was very regular, and we propose an adaptive value scheme (KNJPEG‐LS) to further simplify the hardware circuit. |
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| AbstractList | JPEG‐LS is a lossless/near‐lossless image compression algorithm based on context modeling, which has the advantages of easy implementation, low resource consumption and high compression rate. It is widely used in the compression field of continuous‐tone still images. However, single image compression has significant latency and high hardware resource consumption issues, as the JPEG‐LS algorithm requires pixel by pixel prediction and real‐time context updates during the compression process, which is not conducive to algorithm IP implementation. Based on Demura compensation data compression requirements, this article has made changes to the pixel prediction method of the JPEG‐LS algorithm and delayed the update of the context to solve the compression latency and resource consumption issues. After algorithm optimization (NJPEGLS), the linebuffer resource occupation was reduced by 8/9, the clock frequency reached above 140 MHz, and the comprehensive compression rate loss was within 4.5%, meeting the demand for Demura compensation data compression/decompression. In this paper, we also conducted statistics and analysis on the distribution of values, and found that the distribution of values was very regular, and we propose an adaptive value scheme (KNJPEG‐LS) to further simplify the hardware circuit. |
| Author | Guo, Xingling Chen, Lin Huang, Jiting Wang, Shuaizhao Tan, Xiaoping Zhu, Xiujian Ge, Mingwei |
| Author_xml | – sequence: 1 givenname: Lin surname: Chen fullname: Chen, Lin organization: Hefei Visionox Technology Co., Ltd – sequence: 2 givenname: Shuaizhao surname: Wang fullname: Wang, Shuaizhao organization: Hefei Visionox Technology Co., Ltd – sequence: 3 givenname: Xingling surname: Guo fullname: Guo, Xingling organization: Hefei Visionox Technology Co., Ltd – sequence: 4 givenname: Xiaoping surname: Tan fullname: Tan, Xiaoping organization: Kunshan Govisionox Optoelectronics Co., Ltd – sequence: 5 givenname: Jiting surname: Huang fullname: Huang, Jiting organization: Hefei Visionox Technology Co., Ltd – sequence: 6 givenname: Mingwei surname: Ge fullname: Ge, Mingwei organization: Kunshan Govisionox Optoelectronics Co., Ltd – sequence: 7 givenname: Xiujian surname: Zhu fullname: Zhu, Xiujian organization: Kunshan Govisionox Optoelectronics Co., Ltd |
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| Cites_doi | 10.1109/ICIP.2018.8451577 10.1109/ICEEOT.2016.7755200 10.1109/ICCD53106.2021.00060 |
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| References | 2018 2021 1999; 4 2016 e_1_2_1_5_1 e_1_2_1_6_1 Weinberger M J (e_1_2_1_2_1) 1999 e_1_2_1_4_1 Kumar S N (e_1_2_1_3_1) 2021 |
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| SubjectTerms | Algorithms Compensation Consumption Context Data compression Demand analysis Demura Hardware Image Compression JPEG-LS Pixels |
| Title | 47‐4: A Novel Demura Compensation Data Compression Algorithm based on JPEG‐LS |
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