Visibility of wavelet quantization noise

Abstract

The discrete wavelet transform (DWT) decomposes an image into bands that vary in spatial frequency and orientation. It is widely used for image compression. Measures of the visibility of DWT quantization errors are required to achieve optimal compression. Uniform quantization of a single band of coefficients results in an artifact that we call DWT uniform quantization noise; it is the sum of a lattice of random amplitude basis functions of the corresponding DWT synthesis filter. We measured visual detection thresholds for samples of DWT uniform quantization noise in Y, Cb, and Cr color channels. The spatial frequency of a wavelet is r 2-lambda, where r is display visual resolution in pixels/degree, and lambda is the wavelet level. Thresholds increase rapidly with wavelet spatial frequency. Thresholds also increase from Y to Cr to Cb, and with orientation from lowpass to horizontal/vertical to diagonal. We construct a mathematical model for DWT noise detection thresholds that is a function of level, orientation, and display visual resolution. This allows calculation of a "perceptually lossless" quantization matrix for which all errors are in theory below the visual threshold. The model may also be used as the basis for adaptive quantization schemes.

A Robust Image Authentication Method Based on Wavelet Transform and Teager Energy Operator

“…The proposed approach is based on the discrete wavelet transform (DWT). The DWT has the properties: precise localization ability, excellent multi-scale analysis, and the publicly available masking thresholds [24]; thus it is suitable for the watermarking applications.…”

Interframe wavelet coding—motion picture representation for universal scalability

“…Just noticeable difference thresholds were incorporated into the MC-EZBC coder, and subjective tests were conducted. Just noticeable difference (JND) was determined using the method of [48]. The bit rates were around 50 Mbps and none of the test ensemble of viewers could see the difference.…”

“…A two-alternative forced choice (2AFC) test [48] was employed, where the subjects were shown an original sequence, a pause, a test sequence, a pause, and another testing sequence. One of the testing sequences was the original.…”

Perceptual watermarking for Discrete Shearlet transform

“…Many image watermarking algorithms that utilize visual models to increase the robustness and transparency can be found in [1,12]- [15]. This paper aims to explore further the usage of DST for watermarking and to achieve new standards of imperceptibility by combining visual models and the discrete Shearlet transforms for watermarking.…”