<title>Human chromosome image compression using cascaded differential and wavelet coding</title>

CCD aerial camera is one of the important means of obtaining the image information on the ground, it is through the collection, archiving, and reading to achieved the images acquisition. As the very large amounts of data of the images, it takes a lot of time far more than analysis and processing when archiving and reading, so that not only difficult achieve real-time detection and processing, but also causing a waste of storage space. Therefore, the research of image compression and other processing technology has become important particularly.This paper use the wavelet coding to get images compression for the problem, and design the image processing system of aerial camera manipulator. This system designed by embedded modular, and ARINC 429 bus to achieve communications between the camera and the aircraft systems, make compression to the images which captured by the camera, and deal with the compressed image as stored, local zoom in and out, etc.

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Wavelet Based Image Compression Using Soft Computing Techniques

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.573.477 ◽

2014 ◽

Vol 573 ◽

pp. 477-482

Author(s):

S. Sudhakar Ilango ◽

V. Seenivasagam

Keyword(s):

Image Compression ◽

Space Partitioning ◽

Compression Algorithms ◽

Time Frequency ◽

Bee Colony ◽

Soft Computing Techniques ◽

Wavelet Coding ◽

Binary Space Partitioning ◽

Precise Analysis ◽

The Fourier Transform

The Wavelet Transform is a multi-resolution transform, that is, it allows a form of time–frequency analysis (or translation–scale in wavelet speak). When using the Fourier transform the result is a very precise analysis of the frequencies contained in the signal, but no information on when those frequencies occurred. The wavelet based image compression algorithms are used widely compared with other conventional compression algorithms. The wavelet coding based on the coefficient selection and sub band level. In this paper we have used two wavelets such as spherical and geometric wavelets. The spherical representation is a hierarchical description of how total energy gets distributed within each wavelet sub band.In the proposed method, we used fuzzy quantization technique for coefficient selection in the spherical wavelet. The other scheme introduces binary space partitioning scheme and geometric wavelet, where the existing pruning method of binary space partitioning is replaced by the genetic algorithm. We had another experiment with geometric wavelet with Artificial Bee Colony (ABC) algorithm. The experimental results for all the three methods are discussed in this paper. The advantages of these methods are the improved PSNR values at high and medium bit rates.

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