A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Networks
Color Image Coding based on Embedded Wavelet Zerotree and Scalar Quantization
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Grayscale true two-dimensional dictionary-based image compression
Journal of Visual Communication and Image Representation
Graphics Image Compression Using JPEG2000
CISP '08 Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 1 - Volume 01
Image coding based on a morphological representation of wavelet data
IEEE Transactions on Image Processing
Wavelet-based color image compression: exploiting the contrast sensitivity function
IEEE Transactions on Image Processing
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Increase in the use of color images in the continuous expansion of multimedia applications has increased the demand for efficient techniques that can store and transmit visual information. This demand has made image compression a vital factor and has increased the need for efficient algorithms that can result in high compression ratio with minimum loss. This paper proposes an innovative technique for compressing color still images using wavelet compression scheme. The proposed scheme uses wavelet transformation, tree structured vector quantization and binary vector morphological prediction for compressing color images. Binary vector morphology is used to predict the significance of coefficients in the subbands across different color components. The use of tree structured vector quantization reduced the search time for quantization and coding. This greatly enhanced the proposed algorithm in terms of compression and decompression time. The experimental results revealed that the proposed algorithm produced a high compression ratio with minimum loss.