EZW Image Compression Algorithm

Research in multimedia technology reveals that the EZW (Embedded Zerotree Wavelet) image compression algorithm demonstrates reduced processing speed when handling high-resolution images exceeding 128x128 pixels. This algorithm employs wavelet transformation followed by zerotree coding to maintain image quality during compression, where the encoder progressively refines coefficients through multiple significance passes. However, larger image dimensions substantially increase the number of wavelet coefficients and hierarchical trees requiring processing, directly impacting computational efficiency. The implementation typically involves recursive quadrant scanning for coefficient significance testing and bit-plane coding for embedded bitstream generation. Therefore, when applying the EZW algorithm, careful consideration of image resolution versus processing speed becomes crucial, necessitating potential optimizations like threshold adaptation or parallel processing for practical applications requiring faster throughput.