Image Compression Using Bayer Color Filter Array Technique

Ms. Deepali S. Jadhav; Mr. A. H. Karode; Mr. S. R. Suralkar

The representation of the color image coefficient and its compression is the major problem in today’s current image capturing and compression in camera technology. The issue of higher resolution image capturing for clarity {&} storage at lower resolution is transforming the image where pixel value lost its originality {&} resulting poorer regeneration. An efficient prediction based lossless compression scheme for Bayer color filter array image is proposed in this paper. It divides the Color filter array image into two subimages, a green subimage and nongreen subimage. Both subimages are processed with Context matching prediction technique to remove the spatial dependency and adaptive color difference estimation scheme to remove color spectral redundancy when handling non green samples. The prediction residue planes of the two subimages are then entropy encoded sequentially with adaptive Rice Code. Simulation result shows that proposed compression scheme having better compression ratio and higher PSNR than the other CFA image compression methods.

Select Volume / Issues:

• Volume 3 Issue 5, Sept. 2012

Year:

2012

Type of Publication:

Article

Keywords:

CFA Image; Context matching prediction; Demosaicing; Image Compression

Journal:

IJECCE

Volume:

3

Number:

5

Pages:

1217-1221

Month:

Sept.