A review of the fractal image coding literature

Wohlberg, Brendt; Jager, G. de

doi:10.1109/83.806618

Cited by 237 publications

(95 citation statements)

References 110 publications

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“…For each range block, it exhaustively searches, the domain pool, for a best-matched domain block with the minimum rms error after applying a contractive affine transform to the domain block. The problems that occur in fractal encoding are the computational demands and the existence of best rangedomain matches [5]. However searching the domain pool is highly computationally intensive.…”

Section: ) Fractal Encodingmentioning

confidence: 99%

Application of Quadtree Partitioning in Fractal Image Compression using Error Based Approach

Khedgaonkar¹

2012

IOSRJEN

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Abstract-Fractal image Compression is a lossycompression technique that has been developed in the early 1990s. Fractals can be an effective approach for several applications other than image coding and transmission: database indexing, texture mapping, and even pattern recognition problems such as writer authentication. Fractal image compression has received much attention from the research community because of some desirable properties like resolution independence, fast decoding, and very competitive rate-distortion curves. Despite the advances made, the long computing times in the encoding phase still remain the main drawback of this technique. In Fractal image compression we obtained self similarity in image. The basic scheme of fractal image compression is to partition a given image into non overlapping blocks of size rxr, called range blocks and form a domain pool containing all of possible overlapped blocks of size 2rx2r, called domain blocks associated with 8 isometries from reflections and rotations.We have proposed a method to reduce the complexity of the image coding phase by classifying the blocks according to an approximation error measure. It perform range\domain comparisons with respect to a preset block, in this instead of binary tree we have used B tree. The main application of B tree is the organization of huge collection of records into a file structure i.e., insertion, deletion and modification operation can be carried out perfectly and efficiently. Therefore, it is possible to reduce drastically the amount of operations needed to encode each range. For partitioning an original image into range blocks we have used quadtree partitioning method.

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Section: ) Fractal Encodingmentioning

confidence: 99%

Application of Quadtree Partitioning in Fractal Image Compression using Error Based Approach

Khedgaonkar¹

2012

IOSRJEN

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“…The luminance shift is replaced by the mean which is coded using 8 bits. The contrast scaling α is determined by testing all the values in the following set {n/4, n=1, 2, 3, 4} to find the best one that minimizes the distortion [5] and is stored using 2 bits. On the other hand, the eight isometrics for shuffling the pixels in the block can be coded by three bits.…”

Section: Encodermentioning

confidence: 99%

“…The fractal coding scheme is a technique for image compression [1]- [5]. It has become one of the most popular modern image coding methods in recent years.…”

Section: Introductionmentioning

confidence: 99%

Untitled

2010

IJIVP

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An enhanced iteration free fractal algorithm is proposed in this research paper to design an efficient domain pool for image compression. The proposed methodology reduces the coding process time, intensive computation tasks and also the memory requirements. The redundancies in the domain pool are reduced by the Linde Buzo Gray (LBG) Algorithm. For each range block, vector features such as mean value, edge strength, and texture strength are used to delete the irrelevant domain block. A pruning condition for terminating the searching process to find the best domain block from the domain pool is used. The codes are stored efficiently by comparing the values of the previous coded range blocks. The performance of the proposed method is compared with the existing iteration free fractal code for the benchmark images on the parameters like coding time, memory capacity and image quality. From the results of the computer simulation, the proposed method achieves excellent performance in coding time. The enhancement scheme for iteration free fractal image coding using vector quantization resulted in a reduction of 5.7 times and 11.5 times than the existing iteration free fractal code method for the single block partition of size 8x8 and 4x4 respectively on the Lena image for the codebook of size 16. The reduction in time is still higher in using code books of higher levels.

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“…Fractal image compression (FIC) is based on the theory of Iterated Function System (IFS) which is used to represent the self-similarities of the images and is represented as a finite set of contraction mapping for each image that has the fixed point which is identical to the image itself [6]- [8]. Fractal image compression (FIC) seems to be one of the favorable methods of lossy image compression due to its advantages like resolution independence, high compression ratio, and fast decompression [9]. This technique was initially proposed by Jacquin and is based on the method of lossy compression.…”

Section: Introductionmentioning

confidence: 99%

Fractal Compression Technique for Color Images Using Variable Block

Ahmed¹,

Sattar²

2017

IJIVP

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The main intention of Fractal Image Compression is to reduce the size of image and maintain good level of their reconstructed image. A major issue in Fractal Image Compression is decrease in image quality, compression ratio and PSNR. To overcome these issues we employ Fractal transformation with entropy coding. There are two phases in the proposed approach. In the first phase color images are separated into three RGB planes using variable range block size. In second phase by applying the inverse transform and iterative functions the image is restored. It is observed that the results are improving in fractal compression for both gray images as well as color images. In this work high CR and PSNR is observed compared to fixed block range and other existing methods. The proposed work yields better CR of 20 and high PSNR.

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A review of the fractal image coding literature

Cited by 237 publications

References 110 publications

Application of Quadtree Partitioning in Fractal Image Compression using Error Based Approach

Application of Quadtree Partitioning in Fractal Image Compression using Error Based Approach

Untitled

Fractal Compression Technique for Color Images Using Variable Block

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