A hardware architecture for real-time image compression using a searchless fractal image coding method

被引:0
|
作者
David Jeff Jackson
Haichen Ren
Xianwei Wu
Kenneth G. Ricks
机构
[1] The University of Alabama,Department of Electrical and Computer Engineering
来源
关键词
Fractal image encoding; Quadtree; Searchless; Real-time image compression;
D O I
暂无
中图分类号
学科分类号
摘要
In this paper we present a novel hardware architecture for real-time image compression implementing a fast, searchless iterated function system (SIFS) fractal coding method. In the proposed method and corresponding hardware architecture, domain blocks are fixed to a spatially neighboring area of range blocks in a manner similar to that given by Furao and Hasegawa. A quadtree structure, covering from 32 × 32 blocks down to 2 × 2 blocks, and even to single pixels, is used for partitioning. Coding of 2 × 2 blocks and single pixels is unique among current fractal coders. The hardware architecture contains units for domain construction, zig-zag transforms, range and domain mean computation, and a parallel domain-range match capable of concurrently generating a fractal code for all quadtree levels. With this efficient, parallel hardware architecture, the fractal encoding speed is improved dramatically. Additionally, attained compression performance remains comparable to traditional search-based and other searchless methods. Experimental results, with the proposed hardware architecture implemented on an Altera APEX20K FPGA, show that the fractal encoder can encode a 512 × 512 × 8 image in approximately 8.36 ms operating at 32.05 MHz. Therefore, this architecture is seen as a feasible solution to real-time fractal image compression.
引用
收藏
页码:225 / 237
页数:12
相关论文
共 50 条
  • [21] Color image compression on spiral architecture using optimized domain blocks in fractal coding
    Thakur, Nileshsingh V.
    Kakde, O. G.
    INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY, PROCEEDINGS, 2007, : 234 - +
  • [22] Improved image compression using fractal block coding
    Hashemian, R
    Marivada, S
    Proceedings of the 46th IEEE International Midwest Symposium on Circuits & Systems, Vols 1-3, 2003, : 544 - 547
  • [23] Real-Time Adaptive Image Compression
    Rippel, Oren
    Bourdev, Lubomir
    INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 70, 2017, 70
  • [24] Reconfigurable architecture for real-time image compression on-board satellites
    Manthey, Kristian
    Krutz, David
    Juurlink, Ben
    JOURNAL OF APPLIED REMOTE SENSING, 2015, 9
  • [25] Fractal image coding for emission tomographic image compression
    Wong, KP
    2001 IEEE NUCLEAR SCIENCE SYMPOSIUM, CONFERENCE RECORDS, VOLS 1-4, 2002, : 1376 - 1379
  • [26] Hardware architecture to realize multi-layer image processing in real-time
    Lu, Chieh-Lun
    Fu, Li-Chen
    IECON 2007: 33RD ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY, VOLS 1-3, CONFERENCE PROCEEDINGS, 2007, : 2478 - 2483
  • [27] FPGA-Based Parallel Hardware Architecture for Real-Time Image Classification
    Qasaimeh, Murad
    Sagahyroon, Assim
    Shanableh, Tamer
    IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING, 2015, 1 (01) : 56 - 70
  • [28] FAIR: A hardware architecture for real-time 3-D image registration
    Castro-Pareja, CR
    Jagadeesh, JM
    Shekhar, R
    IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE, 2003, 7 (04): : 426 - 434
  • [29] Hardware Architecture for Real-Time Computation of Image Component Feature Descriptors on a FPGA
    Malik, Abdul Waheed
    Thornberg, Benny
    Imran, Muhammad
    Lawal, Najeem
    INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS, 2014,
  • [30] Configurable hardware architecture for real-time window-based image processing
    Torres-Huitzil, C
    Arias-Estrada, M
    FIELD-PROGRAMMABLE LOGIC AND APPLICATIONS, PROCEEDINGS, 2003, 2778 : 1008 - 1011