Vignan Nirula Institute of technology for women

India

Vignan Nirula Institute of technology for women

India
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Rani B.M.S.,Vignan Nirula Institute of technology for women | Divya Sree M.,Vignan Nirula Institute of technology for women | Ravi T.,Koneru Lakshmaiah College of Engineering
International Journal of Applied Engineering Research | Year: 2015

Wavelet analysis is very powerful and extremely useful for compressing data such as images. Its power comes from its multi resolution. wavelet analysis is done on the entire image rather than sections at a time. A well known application of wavelet analysis is the compression of fingerprint images by the FBI. Changing the decomposition level changes the amount of detail in the decomposition. Thus, at higher decomposition levels, higher compression rates can be gained. Wavelets attempt to approximate how an image is changing, thus the best wavelet to use for an image would be one that approximates the image well. n certain signals, many of the wavelet coefficients are close or equal to zero. Through a method called thresholding, these coefficients may be modified so that the sequence of wavelet coefficients contains long strings of zeros. Through a type of compression known as entropy coding, these long strings may be stored and sent electronically in much less space. There are different types of thresholding. In this paper thresholding based wavelet analysis is been implemented to obtain lossless image compression. And among the thresholding techniques,a hard thresholding technique is been utilized. In hard thresholding, a tolerance is selected. Any wavelet whose absolute value falls below the tolerance is set to zero with the goal to introduce many zeros without losing a great amount of detail. © Research India Publications.


Rani B.M.S.,Vignan Nirula Institute of technology for women | Divya Sree M.,Vignan Nirula Institute of technology for women | Ravi T.,Koneru Lakshmaiah College of Engineering
International Journal of Applied Engineering Research | Year: 2015

The necessity for an efficient technique for compression of Images increasing because the raw images need large amounts of disk space seems to be a big disadvantage during transmission as well as storage. Even though there are so many compression technique already existing a better technique which is faster, memory efficient and simple surely suits the requirements of the user. In this paper we proposed the Lossless technique of image compression and decompression using a simple coding method called Huffman coding. This technique is simple in implementation and utilizes less memory space. An algorithm has been designed and implemented to compress and decompress the given image using Huffman coding techniques in a MATLAB software. © Research India Publications.

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