A low complexity block-based adaptive lossless image compression

被引:3
|
作者
Yang, Long [1 ]
He, Xiaohai [1 ]
Zhang, Gang [2 ]
Qing, Linbo [1 ]
Che, Tiben [1 ]
机构
[1] Sichuan Univ, Image Informat Inst, Coll Elect & Informat Engn, Chengdu 610064, Peoples R China
[2] Chinese Acad Sci, Inst Opt & Elect, Chengdu 610209, Peoples R China
来源
OPTIK | 2013年 / 124卷 / 24期
关键词
Embedded compression; IWT; LHT; FPGA; INTEGER WAVELET TRANSFORM; ALGORITHM;
D O I
10.1016/j.ijleo.2013.05.125
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
For low power and lossless image compression, in this paper, a low complexity, block-based decomposition of subbands technology is proposed for embedded compression (EC) algorithm, which is ready for being implemented on a single-chip of FPGA. The proposed algorithm is based on high-speed pipeline architecture of 2-D lossless integer wavelet transformation (MU) with 2-D Lossless Hadamard Transformation (LHT). In the proposed algorithm, the coefficients of a 2-D IVVT are decomposed by 4 x 4 blocks to further remove redundancy, compared with direct encoder by EBCOT of JPEG2000. Considering the feature of the 2-D IWT, a different strategy is designed for LL-subband and non-LL subbands, which denotes DC prediction (DCP) and adaptive transformation method (ATM), respectively. DCP is used to remove the correlation between two adjacent blocks of LL-subband, and ATM is used to transform non-LL subbands by 2-D LHT selectivity. After further transformation, the coefficients are decomposed as truncated integer part (TIP) and truncated residue parts (TRP), considering the complexity of hardware implementation, TIP is encoded by Zero Running Length (ZRL) and Exp-Golomb (EG). TRP is encoded by a fixed length (FL) encoder after removed redundancy by the feature of 2-D LHT, when seen as bit patterns [1]. Experimental results show that the proposed EC algorithm can achieve a good compression performance as JPEG2000, and the coding latency can be decreased at an average of 43.9%. Another innovation of this paper is EC's hardware-friendly feature and easy hardware implementation, which are presented by a simple addition or subtraction of the LIWT and LHT, and need a small on-chip memory. Crown Copyright (C) 2013 Published by Elsevier GmbH. All rights reserved.
引用
收藏
页码:6545 / 6552
页数:8
相关论文
共 50 条
  • [41] Block-Based Image Compression With Parameter-Assistant Inpainting
    Xiong, Zhiwei
    Sun, Xiaoyan
    Wu, Feng
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2010, 19 (06) : 1651 - 1657
  • [42] Block-based Classification Method for Computer Screen Image Compression
    Wu, Kai
    Gahan, Richard
    O'Friel, Patrick
    2018 29TH IRISH SIGNALS AND SYSTEMS CONFERENCE (ISSC), 2018,
  • [43] Region Based Medical Image compression Using Block-Based PCA
    Kiran, Ravi
    Kamargaonkar, Chandrashekhar
    2016 INTERNATIONAL CONFERENCE ON COMPUTATION OF POWER, ENERGY INFORMATION AND COMMUNICATION (ICCPEIC), 2016, : 91 - 96
  • [44] Adaptive predictor for lossless image compression
    Hlavác, V
    Fojtík, J
    COMPUTING, 1999, 62 (04) : 339 - 354
  • [45] Block-based conditional entropy coding for medical image compression
    Kumar, SVB
    Nagaraj, N
    Mukhopadhyay, S
    Xu, XF
    MEDICAL IMAGING 2003: PACS AND INTEGRATED MEDICAL INFORMATION SYSTEMS: DESIGN AND EVALUATION, 2003, 5033 : 375 - 381
  • [46] An adaptive coder for lossless image compression
    Li, S
    Cao, L
    ISTM/2003: 5TH INTERNATIONAL SYMPOSIUM ON TEST AND MEASUREMENT, VOLS 1-6, CONFERENCE PROCEEDINGS, 2003, : 1847 - 1847
  • [47] Adaptive Predictor for Lossless Image Compression
    V. Hlaváč
    J. Fojtík
    Computing, 1999, 62 : 339 - 354
  • [48] Adaptive predictor for lossless image compression
    Center for Machine Perception, Faculty of Electrical Engineering, Czech Technical University, Karlovo namesti 13, 121 35 Prague 2, Czech Republic
    Comput Vienna New York, 4 (339-354):
  • [49] Adaptive prediction for lossless image compression
    Marusic, S
    Deng, G
    SIGNAL PROCESSING-IMAGE COMMUNICATION, 2002, 17 (05) : 363 - 372
  • [50] LOCO-I: A low complexity, context-based, lossless image compression algorithm
    Weinberger, MJ
    Seroussi, G
    Sapiro, G
    DCC '96 - DATA COMPRESSION CONFERENCE, PROCEEDINGS, 1996, : 140 - 149