2 research outputs found
Analysis of the DCT coefficient distributions for document coding
It is known that the distribution of the discrete cosine transform (DCT) coefficients of most natural images follow a Laplacian distribution, and this knowledge has been employed to improve decoder design. However, such is not the case for text documents. In this letter, we present an analysis of their DCT coefficient distributions, and show that a Gaussian distribution can be a realistic model. Furthermore, we can use a generalized Gaussian model to incorporate the Laplacian distribution found for natural images.published_or_final_versio
Recovering Sign Bits of DCT Coefficients in Digital Images as an Optimization Problem
Recovering unknown, missing, damaged, distorted or lost information in DCT
coefficients is a common task in multiple applications of digital image
processing, including image compression, selective image encryption, and image
communications. This paper investigates recovery of a special type of
information in DCT coefficients of digital images: sign bits. This problem can
be modelled as a mixed integer linear programming (MILP) problem, which is
NP-hard in general. To efficiently solve the problem, we propose two
approximation methods: 1) a relaxation-based method that convert the MILP
problem to a linear programming (LP) problem; 2) a divide-and-conquer method
which splits the target image into sufficiently small regions, each of which
can be more efficiently solved as an MILP problem, and then conducts a global
optimization phase as a smaller MILP problem or an LP problem to maximize
smoothness across different regions. To the best of our knowledge, we are the
first who considered how to use global optimization to recover sign bits of DCT
coefficients. We considered how the proposed methods can be applied to
JPEG-encoded images and conducted extensive experiments to validate the
performances of our proposed methods. The experimental results showed that the
proposed methods worked well, especially when the number of unknown sign bits
per DCT block is not too large. Compared with other existing methods, which are
all based on simple error-concealment strategies, our proposed methods
outperformed them with a substantial margin, both according to objective
quality metrics (PSNR and SSIM) and also our subjective evaluation. Our work
has a number of profound implications, e.g., more sign bits can be discarded to
develop more efficient image compression methods, and image encryption methods
based on sign bit encryption can be less secure than we previously understood.Comment: 13 pages, 8 figure