New Lossless Compression Algorithms for Transport Images

2021 ◽  
Vol 27 (6) ◽  
pp. 299-305
Author(s):  
S. Sh. Fahmi ◽  
◽  
A. G. Davidchuk ◽  
E. V. Kostikova ◽  
◽  
...  
Keyword(s):  
Image Compression ◽  
Spectral Region ◽  
Lossless Compression ◽  
Source Image ◽  
Surveillance Systems ◽  
Recursive Method ◽  
Original Signal ◽  
Series Length ◽  
Compression Algorithms ◽  
New Algorithms

The article considers the relevance of the development of lossless image compression and transmission algorithms and their application for creating transport video surveillance systems. A brief overview of lossless transport image compression methods is provided. We propose a method for compressing transport plots based on the pyramid-recursive method of splitting the source image into polygons of various shapes and sizes. We consider two new algorithms for implementing the proposed method that are fundamentally different from each other: with a transition to the spectral region and without a transition to the spectral region of the original signal to ensure lossless compression. The results of testing various well-known lossless compression algorithms are analyzed: series length, Huffman, and arithmetic encoding, and compared with the proposed algorithms. It is shown that the proposed algorithms are more efficient in terms of compression ratio (2—3 times) compared to the known ones, while the computational complexity increases approximately by more than 3-4 times.

Efficient Image Compression Algorithms Using Evolved Wavelets

2011 ◽  
Vol 1 (4) ◽  
pp. 1-8
Author(s):  
G. Chenchu Krishnaiah ◽  
T. Jayachandraprasad ◽  
M.N. Giri Prasad
Keyword(s):  
Image Compression ◽  
Compression Algorithms

ESTIMATION OF HYBRID IMAGE COMPRESSION ALGORITHMS FOR UNDERWATER IMAGES

2018 ◽  
Vol 5 (4) ◽  
pp. 34
Author(s):  
R. PANDIAN ◽  
KUMARI S. LALITHA ◽  
KUMAR R. RAJA ◽  
RAVIKUMAR D. N. S. ◽  
◽  
...  
Keyword(s):  
Image Compression ◽  
Compression Algorithms

Enhanced Three-Dimensional Color Conversion Based on Discrete Wavelet Transform

2012 ◽  
Vol 155-156 ◽  
pp. 440-444
Author(s):  
He Yan ◽  
Xiu Feng Wang
Keyword(s):  
Information Technology ◽  
Wavelet Transform ◽  
Image Reconstruction ◽  
Image Quality ◽  
Image Compression ◽  
High Performance ◽  
Three Dimensional ◽  
Discrete Wavelet ◽  
Compression Algorithms ◽  
Color Conversion

JPEG2000 algorithm has been developed based on the DWT techniques, which have shown how the results achieved in different areas in information technology can be applied to enhance the performance. Lossy image compression algorithms sacrifice perfect image reconstruction in favor of decreased storage requirements. Wavelets have become a popular technology for information redistribution for high-performance image compression algorithms. Lossy compression algorithms sacrifice perfect image reconstruction in favor of improved compression rates while minimizing image quality lossy.

APPLICATION OF GENETIC ALGORITHM FOR IMAGE TRANSFER

2020 ◽  
Vol 1 (2) ◽  
pp. 44-51
Author(s):  
Paula Pereira ◽  
Tanara Kuhn
Keyword(s):  
Genetic Algorithm ◽  
Lossless Compression ◽  
Search Method ◽  
Source Image ◽  
Image Transfer ◽  
Target Image ◽  
Mosaic Image ◽  
Permutation Array

For images transfer, different embedding system exist which works by creating a mosaic image from the source image and recovery from the target image using some sort of algorithm. In current study, a method is proposed using the genetic algorithm for recovery of image from the source image. The algorithm utilized is genetic algorithm which is a search method along with another additional technique for obtaining higher robustness and security. The proposed methodology works by dividing the source image into smaller parts which are fitted into target image using the lossless compression. The mosaic image is recovered at retrieving side by the permutation array which is recovered and mapped using the pre-select key.

scholarly journals The Hyper-spectral Image Compression Based on K-Means Clustering and Parallel Prediction Algorithm*

2018 ◽  
Vol 173 ◽  
pp. 03071
Author(s):  
Wu Wenbin ◽  
Yue Wu ◽  
Jintao Li
Keyword(s):  
Image Compression ◽  
Clustering Algorithm ◽  
Compression Algorithm ◽  
Prediction Algorithm ◽  
Two Dimensional ◽  
Spectral Image ◽  
Compression Algorithms ◽  
Serial Processing ◽  
Compression Time ◽  
Hyper Spectral

In this paper, we propose a lossless compression algorithm for hyper-spectral images with the help of the K-Means clustering and parallel prediction. We use K-Means clustering algorithm to classify hyper-spectral images, and we obtain a number of two dimensional sub images. We use the adaptive prediction compression algorithm based on the absolute ratio to compress the two dimensional sub images. The traditional prediction algorithm is adopted in the serial processing mode, and the processing time is long. So we improve the efficiency of the parallel prediction compression algorithm, to meet the needs of the rapid compression. In this paper, a variety of hyper-spectral image compression algorithms are compared with the proposed method. The experimental results show that the proposed algorithm can effectively improve the compression ratio of hyper-spectral images and reduce the compression time effectively.

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