scholarly journals A PREDICTIVE CODING METHOD FOR LOSSLESS COMPRESSION OF IMAGES

2013 ◽  
Vol 7 (3) ◽  
pp. 683-685
Author(s):  
Anil Mishra ◽  
Ms. Savita Shiwani
Keyword(s):  
Image Compression ◽  
Image Coding ◽  
Video Processing ◽  
Prediction Method ◽  
Original Form ◽  
Minimum Entropy ◽  
Digital World ◽  
Adaptive Prediction ◽  
Continuous Tone ◽  
Spatial Redundancy

Images are an important part of today's digital world. However, due to the large quantity of data needed to represent modern imagery the storage of such data can be expensive. Thus, work on efficient image storage (image compression) has the potential to reduce storage costs and enable new applications.This lossless image compression has uses in medical, scientific and professional video processing applications.Compression is a process, in which given size of data is compressed to a smaller size. Storing and sending images to its original form can present a problem in terms of storage space and transmission speed.Compression is efficient for storing and transmission purpose.In this paper we described a new lossless adaptive prediction based algorithm for continuous tone images. In continuous tone images spatial redundancy exists.Our approach is to develop a new backward adaptive prediction techniques to reduce spatial redundancy in a image.The new prediction technique known as Modifed Gradient Adjusted Predictor (MGAP) is developed. MGAP is based on the prediction method used in Context based Adaptive Lossless Image Coding (CALIC). An adaptive selection method which selects the predictor in a slope bin in terms of minimum entropy improves the compression performance.

scholarly journals Soft Compression for Lossless Image Coding Based on Shape Recognition

Entropy ◽  
2021 ◽  
Vol 23 (12) ◽  
pp. 1680
Author(s):  
Gangtao Xin ◽  
Pingyi Fan
Keyword(s):  
Image Compression ◽  
Image Coding ◽  
Storage Space ◽  
Compression Method ◽  
Lossless Image Compression ◽  
Working Principle ◽  
Spatial Redundancy ◽  
And Storage ◽  
Component Image ◽  
Do So

Soft compression is a lossless image compression method that is committed to eliminating coding redundancy and spatial redundancy simultaneously. To do so, it adopts shapes to encode an image. In this paper, we propose a compressible indicator function with regard to images, which gives a threshold of the average number of bits required to represent a location and can be used for illustrating the working principle. We investigate and analyze soft compression for binary image, gray image and multi-component image with specific algorithms and compressible indicator value. In terms of compression ratio, the soft compression algorithm outperforms the popular classical standards PNG and JPEG2000 in lossless image compression. It is expected that the bandwidth and storage space needed when transmitting and storing the same kind of images (such as medical images) can be greatly reduced with applying soft compression.

Mycielski Based 2d-Predictive Image Coding Algorithm

2016 ◽  
Vol 850 ◽  
pp. 144-151 ◽  
Author(s):  
Mehmet Fidan ◽  
Ömer Nezih Gerek
Keyword(s):  
Image Coding ◽  
Predictive Coding ◽  
Prediction Method ◽  
Physical Distance ◽  
Prediction Algorithm ◽  
Two Dimensional ◽  
Two Dimensional Image ◽  
Past Data ◽  
And Performance ◽  
Definition Of

The Mycielski method is a prospering prediction algorithm which is based on searching and finding largest repeated binary patterns. It uses infinite-past data to devise a rule based prediction method on a time series. In this work, a novel two-dimensional (image processing) version of the Mycielski algorithm is proposed. Since the dimensionality definition of “past” data increases in two-dimensional signals, the proposed algorithm also needs to handle how the boundaries of the pixel cliques are iteratively extended in the neighborhood of a current pixel. The clique extension invokes novel similarity search strategies that depend on the chosen physical distance metric. The proposed prediction algorithm is used for predictive image compression and performance comparisons with other predictive coding methods are presented.

AN IMPROVED EMBEDDED ZEROTREE WAVELET IMAGE CODING METHOD BASED ON COEFFICIENT PARTITIONING USING MORPHOLOGICAL OPERATION

2000 ◽  
Vol 14 (06) ◽  
pp. 795-807 ◽  
Author(s):  
JUNMEI ZHONG ◽  
C. H. LEUNG ◽  
Y. Y. TANG
Keyword(s):  
Image Compression ◽  
Video Coding ◽  
Image Coding ◽  
Experimental Results ◽  
Morphological Operation ◽  
Compression Algorithms ◽  
Still Image ◽  
Coding Method ◽  
Wavelet Image ◽  
Image Compression Algorithm

In recent years, wavelets have attracted great attention in both still image compression and video coding, and several novel wavelet-based image compression algorithms have been developed so far, one of which is Shapiro's embedded zerotree wavelet (EZW) image compression algorithm. However, there are still some deficiencies in this algorithm. In this paper, after the analysis of the deficiency in EZW, a new algorithm based on quantized coefficient partitioning using morphological operation is proposed. Instead of encoding the coefficients in each subband line-by-line, regions in which most of the quantized coefficients are significant are extracted by morphological dilation and encoded first. This is followed by using zerotrees to encode the remaining space which has mostly zeros. Experimental results show that the proposed algorithm is not only superior to the EZW, but also compares favorably with the most efficient wavelet-based image compression algorithms reported so far.

Implementation of LOCO-I Lossless Image Compression Algorithm for Deep Space Applications

2014 ◽  
Vol 3 (3) ◽  
pp. 98
Author(s):  
P. Praveena
Keyword(s):  
Image Compression ◽  
Image Coding ◽  
Low Complexity ◽  
Vital Role ◽  
Space Science ◽  
Compression Algorithm ◽  
Deep Space ◽  
Space Applications ◽  
Lossless Image Compression ◽  
Image Compression Algorithm

<p>Present emerging trend in space science applications is to explore and utilize the deep space. Image coding in deep space communications play vital role in deep space missions. Lossless image compression has been recommended for space science exploration missions to retain the quality of image. On-board memory and bandwidth requirement is reduced by image compression. Programmable logic like field programmable gate array (FPGA) offers an attractive solution for performance and flexibility required by real time image compression algorithms. The powerful feature of FPGA is parallel processing which allows the data to process quicker than microprocessor implementation. This paper elaborates on implementing low complexity lossless image compression algorithm coder on FPGA with minimum utilization of onboard resources for deep space applications.</p>

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