Fractal Image Compression is one of the lossy image compression technique where we can obtain a large amount of compression by representing an image as a contractive affine transform. But the main drawback of FIC is its encoding complexity and lack of speed. At the same time it has several advantages such as we can zoom images without degrading the quality due to its resolution independent nature. Similarly DWT (Discrete Wavelet Transform) is one of the most commonly used compression scheme where we obtain best compression. But for a required PSNR the CR of DWT is lesser than the FIC. There are several researches going on in combining these two methods. Here we study the possible techniques to combine the fractal image compression with the wavelet and a new gradient based method for reducing the encoding time.
Arjun Purushothaman : M tech Scholar Department of Electronics and Communication Engineering,
L.B.S College of Engineering, Kasaragod , Kerala, India
Sheeba K : Associate Professor, Department of Electronics and Communication Engineering,
L.B.S College of Engineering, Kasaragod, Kerala, India
Fractal Image compression, Discrete Wavelet Transform, Compression Ratio, Peak Signal to Noise Ratio, Encoding Time
A new gradient based hybrid wavelet-fractal image compression technique is presented here. WFC alone can reduce the encoding time required but by comparing with BFIC image quality is also reduces. The proposed method used here increases the image quality into an acceptable range also maintain other two parameters. Also by comparing the proposed method with FIC using soft computing techniques the proposed method can reduce the encoding time required with an acceptable PSNR.
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