Fractal image compression using upper bound on scaling parameter

被引:19
作者
Roy, Swalpa Kumar [1 ]
Kumar, Siddharth [2 ]
Chanda, Bhabatosh [3 ]
Chaudhuri, Bidyut B. [1 ]
Banerjee, Soumitro [4 ]
机构
[1] Indian Stat Inst, Comp Vis & Pattern Recognit Unit, Kolkata 700108, India
[2] San Jose Sate Univ, Dept Comp Sci, San Jose, CA 95192 USA
[3] Indian Stat Inst, Elect & Commun Sci Unit, Kolkata 700108, India
[4] Indian Inst Sci Educ & Res, Dept Phys Sci, Mohanpur Campus, Kolkata 741246, India
关键词
Fractal coding speedup; Scaling parameter upper-bound; Image data compression; TRANSFORMATION;
D O I
10.1016/j.chaos.2017.11.013
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
This paper presents a novel approach to calculate the affine parameters of fractal encoding, in order to reduce its computational complexity. A simple but efficient approximation of the scaling parameter is derived which satisfies all properties necessary to achieve convergence. It allows us to substitute to the costly process of matrix multiplication with a simple division of two numbers. We have also proposed a modified horizontal-vertical (HV) block partitioning scheme, and some new ways to improve the encoding time and decoded quality, over their conventional counterparts. Experiments on standard images show that our approach yields performance similar to the state-of-the-art fractal based image compression methods, in much less time. (c) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:16 / 22
页数:7
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