title: Direction-adaptive discrete wavelet transform for image compression.
abstract: We propose a direction-adaptive DWT (DA-DWT) that locally adapts the filtering directions to image content based on directional lifting. With the adaptive transform, energy compaction is improved for sharp image features. A mathematical analysis based on an anisotropic statistical image model is presented to quantify the theoretical gain achieved by adapting the filtering directions. The analysis indicates that the proposed DA-DWT is more effective than other lifting-based approaches. Experimental results report a gain of up to 2.5 dB in PSNR over the conventional DWT for typical test images. Subjectively, the reconstruction from the DA-DWT better represents the structure in the image and is visually more pleasing.
authors.affiliation: Information Systems Laboratory, Stanford, CA 94305, USA. chuoling@stanford.edu
authors.forename: Chuo-Ling
authors.initials: CL
authors.lastname: Chang
authors.forename: Bernd
authors.initials: B
authors.lastname: Girod
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D044962:Data Compression / Q000379:methods*; D003627:Data Interpretation, Statistical; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D015233:Models, Statistical; D009716:Numerical Analysis, Computer-Assisted; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted