Gradient match and side match fractal vector quantizers for images

Chang, Hsuan-Ting

doi:10.1109/83.977877

Cited by 15 publications

(3 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The conditions that the parent range block is partitioned into four child range blocks can refer to our previous work. 37,43 Table 3 shows the rate-PSNR performance of two test images. In the cases of the mating ratios r = 0.5 for the Lena image and r = 0.75 for the Peppers image, the maximum PSNRs and minimum bit rates are obtained.…”

Section: Resultsmentioning

confidence: 99%

Intersecured joint image compression with encryption purpose based on fractal mating coding

Chang

Lin

2007

Opt. Eng

View full text Add to dashboard Cite

In this study, a pioneer secure coding concept for pairwise images is revealed and implemented by the use of the proposed fractal mating coding scheme, in which the domain pools consist of the domain blocks selected from the pairwise images to explore both the intra-and inter-image similarities. In addition to the pairwise relation, the mating ratios denoting the percentages of the domain blocks selected from both images are utilized. Further encryption can be achieved by the use of block mean permutation and mating of the fractal codes. The security level is high because that the jointly coded images cannot be correctly reconstructed without all the required information. The computer experiments show that the coding performance can be greatly improved from conventional fractal coding schemes and the inter-secured purpose for pairwise images is successfully achieved.

show abstract

Section: Resultsmentioning

confidence: 99%

Intersecured joint image compression with encryption purpose based on fractal mating coding

Chang

Lin

2007

Opt. Eng

View full text Add to dashboard Cite

show abstract

“…Many papers have been published in this field during the last two decades. Some of them deal more specially with the memory size required to encode the compressed image [12]. Others study the optimization of correspondence search between similar elements in the image ( [10], [13], [14], [15], [16], [17]).…”

Section: ( ) ( )mentioning

confidence: 99%

Texture Learning by Fractal Compression

Dolez¹,

Vincent²

2007

Proceedings of the 7th International Workshop on Pattern Recognition in Information Systems

View full text Add to dashboard Cite

This paper proposes a texture learning method based on fractal compression. This type of compression is efficient for extracting self-similarities in an image. Square blocks are studied and similarities between them highlighted. This allows establishing a score and thus a rating of the blocks. Selecting the blocks that best encode the biggest part of the image or a texture leads to a database of the most representative ones. The recognition step consists in labeling blocks and pixels of a new image. The blocks of the new image are matched with the ones of the different texture databases. As an application, we used our method to recognize vegetation and buildings on aerial images.

show abstract

“…In practical implementations the search-based domain-range matching procedure normally used in fractal image compression naturally introduces significant intensive computational requirements and an unacceptably long compression time [6,9,8,19,11,20,5,16,2]. This is true even for improved methods that have been recently introduced [8,2,15,17].…”

Section: Introductionmentioning

confidence: 98%

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

Jackson

Ren

et al. 2007

J Real-Time Image Proc

View full text Add to dashboard Cite

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 searchbased 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.

show abstract

Gradient match and side match fractal vector quantizers for images

Cited by 15 publications

References 17 publications

Intersecured joint image compression with encryption purpose based on fractal mating coding

Intersecured joint image compression with encryption purpose based on fractal mating coding

Texture Learning by Fractal Compression

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

Contact Info

Product

Resources

About