Learned image compression has achieved great success due to its excellent modeling
capacity, but seldom further considers the Rate-Distortion Optimization (RDO) of each input …

The emerging field semantic communication is driving the research of end-to-end data
transmission. By utilizing the powerful representation ability of deep learning models …

Traditional image editing techniques cannot be directly used to process stereoscopic media,
as extra constraints are required to ensure consistent changes between the left and right …

Low-rank matrix approximation (LRMA) is a powerful technique for signal processing and
pattern analysis. However, its potential for data compression has not yet been fully …

Transform, as one of the most important modules of mainstream video coding systems,
seems very stable over the past several decades. However, recent developments indicate …

Traditional tensor decomposition methods, eg, two dimensional principal component
analysis and two dimensional singular value decomposition, that minimize mean square …

Full-field laser speckle microscopy provides real-time imaging of superficial blood flow rate.
Here we apply continuous wavelet transform to time series of speckle-estimated blood flow …

Transform has been widely used to remove spatial redundancy of prediction residuals in the
modern video coding standards. However, since the residual blocks exhibit diverse …

This paper is dedicated to fast video coding based on three-dimensional discrete wavelet
transform. First, we propose a novel low-complexity bit-plane entropy coding of wavelet …

This paper presents a robust color image watermarking algorithm, which embeds a
grayscale image into a color image using the higher order singular value decomposition …