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영어

This paper proposes image compression in different color spaces using hybrid wavelet transform. To generate hybrid wavelet transform Discrete Kekre transform (DKT) and Discrete Cosine transform (DCT) are selected as component transforms. Due to high energy compaction property, DCT is selected as local component transform that contributes to local features of an image. Hybrid wavelet transform extracts features of both the component transforms and hence gives less error and better image quality. Component transforms of different sizes are selected to generate hybrid wavelet of size 256x256 and applied on images. In RGB color space 16-16 combination i.e. hybrid wavelet generated using DKT 16x16 and DCT 16x16 gives least error than other combinations like 8-32, 32-8 and 64-4. RMSE, MAE, AFCPV and Structural Similarity Index (SSIM) are the error metrics used to measure reconstructed image quality. Different color spaces have been used to observe the performance of this hybrid wavelet transform. In KLUV color space minimum RMSE and MAE is observed than RGB, YUV, YCbCr, XYZ and YIQ color space. Whereas RGB color space gives lowest AFCPV than other color spaces using 16-16 component size. Hence SSIM is used to eliminate this inconsistency in these traditional error metrics. KLUV color space gives highest SSIM 0.998 which is closest to maximum one proving it as a better choice than other color spaces.