Efficiency of analytical transforms for image compression

Compression of medical images by quaternionic wavelet transform

“…showed that analytical transformations have an important role in decorrelation of grayscale images, energy compaction of the image and hardly affect the performance of the compression technique. They discussed the importance of image compression coding systems by comparing the bit rate reduction capability and signal-to-noise ratio of five transforms, namely the Karhunen-Loeve transform (KLT) to the cosine transform discrete transform (DCT), Hartly transform (DHT), discrete Gabor transform (DGT) and discrete wavelet transform (DWT) [11]. Comparative exploitation of compression methods such as Discrete Cosine Transform (DCT), Wavelet Transform (DWT), wavelet packets and b-splines shows that the b-spline compression technique is more suitable for ElectroMyographic (EMG) signal compression [12].…”

Technique of Image Compression: A Review

“…In this method, they implemented the SPIHT and EZW and algorithms with huffman encoder [6],which is used dissimilar of wavelet for compressing and after that comparing between the PSNR and rates of bit for these families are created. These methods were executed on different images, and it is given the results have good quality and it also gives maximal ratio of compression as comparing with the previous existing lossless image compression methods [7]. Also, by Mohammed Otair and Alshami are presented lossless preprocessing method that improves the lossy methods through making a minimize rates of distortion in the compression.…”