Perceptual Image Compression Using Jpeg2000

Image sizes have increased exponentially in recent years. The resulting highresolution images are typically encoded in a lossy fashion to achieve high compression ratios. Lossy compression can be categorized into visually lossless and visually lossy compression depending on the visibility of compression artifacts. This dissertation proposes visually lossless coding methods as well as a visually lossy coding method with perceptual quality control. All resulting codestreams are JPEG2000 Part-I compliant. Visually lossless coding is increasingly considered as an alternative to numerically lossless coding. In order to hide compression artifacts caused by quantization, visibility thresholds (VTs) are measured and used for quantization of subbands in JPEG2000. In this work, VTs are experimentally determined from statistically modeled quantization distortion, which is based on the distribution of wavelet coefficients and the dead-zone quantizer of JPEG2000. The resulting VTs are adjusted for locally changing background through a visual masking model, and then used to determine the minimum number of coding passes to be included in a codestream for visually lossless quality under desired viewing conditions. The proposed coding scheme successfully yields visually lossless images at competitive bitrates compared