Space-Frequency Quantization using Directionlets

In our previous work [1], we proposed a construction of critically sampled perfect reconstruction transforms with directional vanishing moments (DVMs) imposed in the corresponding basis functions along different directions, called directionlets. Here, we combine the directionlets with the space-frequency quantization (SFQ) image compression method, originally based on the standard two-dimensional (2-D) wavelet transform (WT) and proposed in [2]. We show that our new compression method outperforms the standard SFQ as well as the state-of-the-art compression methods, like SPIHT and JPEG2000, in terms of the quality of compressed images, especially in a low-rate compression regime. We also show that the order of computational complexity remains the same, as compared to the complexity of the standard SFQ algorithm.

• Type: Conference
• Year: 2007
• Where: ICIP
• Authors: Vladan Velisavljevic, Baltasar Beferull-Lozano, Martin Vetterli
• Keywords: Compression Methods, Directional Vanishing Moments, ICIP 2007, Image Compression Method, Image Processing