Fractal Color Image Compression by Adaptive Zero-Mean Method

George, Loay E.; Al-Hilo, Eman A.

doi:10.1109/icctd.2009.150

Cited by 8 publications

(5 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…George and Al-Hilo [24] presented an enhancement to the previous method proposed in [22], in which the compression ratio is increased by 3% by using DPCM and shift coding for encoding the range mean and scale parameters. In addition, this method decreases encoding time by 66% and enhances the PSNR at around 5.3%.…”

Section: Fractal Image Compressionmentioning

confidence: 99%

Image and audio fractal compression: comprehensive review, enhancements and research directions

Ali

Abbas²,

George

et al. 2019

IJEECS

View full text Add to dashboard Cite

<p>This study aims to review the recent techniques in digital multimedia compression with respect to fractal coding techniques. It covers the proposed fractal coding methods in audio and image domain and the techniques that were used for accelerating the encoding time process which is considered the main challenge in fractal compression. This study also presents the trends of the researcher's interests in applying fractal coding in image domain in comparison to the audio domain. This review opens directions for further researches in the area of fractal coding in audio compression and removes the obstacles that face its implementation in order to compare fractal audio with the renowned audio compression techniques.</p>

show abstract

Section: Fractal Image Compressionmentioning

confidence: 99%

Image and audio fractal compression: comprehensive review, enhancements and research directions

Ali

Abbas²,

George

et al. 2019

IJEECS

View full text Add to dashboard Cite

show abstract

“…Suppose that each range block have pixel intensities (r 1 ,..,r n ) and each domain block have pixel intensities (d 1 ,..,d n ). Then for each range block (r i ) the optimal affine approximation can be represented as [8,12].…”

Section: Ifs Mappingmentioning

confidence: 99%

“…Some proposed methods involves combination of fractal coding; either using cosine transform (DCT) [5], or Wavelet transform [6]. Other coding methods are based on using moment descriptor as a criteria to classify the range-domain blocks [7,8].…”

Section: Introductionmentioning

confidence: 99%

The Use of Double Moment Based Descriptors to Speed up FIC

Mahmoud¹

2012

JNUS

View full text Add to dashboard Cite

In this research, an improved Partitioned Iterated Function System (PIFS) scheme is introduced to speed up the encoding stage time in Fractal Image Compression (FIC). The proposed system is based on using both symmetry prediction and blocks indexing to speed up the block matching process; these two methods have been used to manage the way of selecting the suitable domain to represent the range block. For block indexing the moment features have been used for determining double block descriptors, each one is affine invariant. The two block descriptors are utilized in a combined indexing scheme to classify the blocks of both range and domain pool. So, the block indexing method is introduced to filter the domain blocks, and keeps only those domain blocks have similar block indices with that of the mapped range block which will be approximately represented using affine mapping. The symmetry predictor is used to reduce the number of isometric trails from 8 to one trail .The research also includes the implementation of the use of single moment descriptor to speed up FIC for comparison. The test results indicated that the proposed improvement has reduced the required encoding time to 0.25 second, and the attain compression ratio is 7.99 without making significant degradation in image quality.

show abstract

“…Applications of fractal coding to color images [36][37][38] are also studied. It is fortunate that human visual system uses only three color channels to encode color information that is sent to the brain.…”

Section: Literature Reviewmentioning

confidence: 99%

Fractal based Image Compression Techniques

Kadam¹,

Rathod²

2017

IJCA

View full text Add to dashboard Cite

Fractal image compression offers high compression ratios and quality image reconstruction. It uses various techniques as the fractal with DCT, wavelet, neural network, genetic algorithms, quantum acceleration etc. Additionally, because fractals are infinitely magnifiable, fractal compression is resolution independent and so a single compressed image can be used efficiently for display in any image resolution including resolution higher than the resolution of the original image. Breaking an image into pieces and identifying selfsimilar ones is the main principle of the approach. In this paper, the different issues in fractal image compression as partitioning, larger encoding time, compression ratio, quality of the reconstructed image, decoding time, SSIM(Structured Similarity Index) are discussed and highlighted. The various areas for improvement as larger encoding time and PSNR are also suggested. The various parameters for evaluating the performance of these techniques as PSNR, compression ratio, encoding time, and decoding time are also suggested. Comparison of Fractal techniques for color image, texture and satellite image is done using different parameters as compression time, compression ratio and PSNR. The hybrid method which combines Fractal quad tree with wavelet and Huffman coding is implemented and compared different parameters as compression ratio and the compression time of the proposed method with the existing methods.

show abstract

Fractal Color Image Compression by Adaptive Zero-Mean Method

Cited by 8 publications

References 7 publications

Image and audio fractal compression: comprehensive review, enhancements and research directions

Image and audio fractal compression: comprehensive review, enhancements and research directions

The Use of Double Moment Based Descriptors to Speed up FIC

Fractal based Image Compression Techniques

Contact Info

Product

Resources

About