Digital Image Compression Through Wavelet Transforms

Recently the massive use of digital images generates increasingly significant volumes of data. Compressing these digital images is thus necessary in order to store them and simplify their transmission. This paper presents an effective algorithm to compress and to reconstruct the digital image. Digital images are decomposed using Biorsplines (bior 6.8)-Biorthogonal Discrete Wavelet Transform (DWT). The wavelet coefficients are encoded using Set Partitioning In Hierarchical Trees (SPIHT). Consistent quality images are generated by this method at a lower bit rate compared to JPEG compression algorithm. The image quality is evaluated in terms of Peak Signal to Noise Ratio (PSNR), Compression Ratio (CR) and Mean Square Error (MSE) for two dimensional still images. Experimental results show that this SPIHT quantization method is simple, efficient, resource saving, and is suitable for real time and low memory implementation.