Improved image recovery from compressed data contaminated with impulsive noise

Compressed sensing (CS) is a new information sampling theory for acquiring sparse or compressible data with much fewer measurements than those otherwise required by the Nyquist/Shannon counterpart. This is particularly important for some imaging applications such as magnetic resonance imaging or in astronomy. However, in the existing CS formulation, the use of the â„“ 2 norm on the residuals is not particularly efficient when the noise is impulsive. This could lead to an increase in the upper bound of the recovery error. To address this problem, we consider a robust formulation for CS to suppress outliers in the residuals. We propose an iterative algorithm for solving the robust CS problem that exploits the power of existing CS solvers. We also show that the upper bound on the recovery error in the case of non-Gaussian noise is reduced and then demonstrate the efficacy of the method through numerical studies.

Nonnegative Matrix Factorization Applied to Nonlinear Speech and Image Cryptosystems

Nonnegative matrix factorization (NMF) is widely used in signal separation and image compression. Motivated by its successful applications, we propose a new cryptosystem based on NMF, where the nonlinear mixing (NLM) model with a strong noise is introduced for encryption and NMF is used for decryption. The security of the cryptosystem relies on following two facts: 1) the constructed multivariable nonlinear function is not invertible; 2) the process of NMF is unilateral, if the inverse matrix of the constructed linear mixing matrix is not nonnegative. Comparing with Lin's method (2006) that is a theoretical scheme using one-time padding in the cryptosystem, our cipher can be used repeatedly for the practical request, i.e., multitme padding is used in our cryptosystem. Also, there is no restriction on statistical characteristics of the ciphers and the plaintexts. Thus, more signals can be processed (successfully encrypted and decrypted), no matter they are correlative, sparse, or Gaussian. Furthermore, instead of the number of zero-crossing-based method that is often unstable in encryption and decryption, an improved method based on the kurtosis of the signals is introduced to solve permutation ambiguities in waveform reconstruction. Simulations are given to illustrate security and availability of our cryptosystem.

Implementation of soft processor based SOC for JPEG compression on FPGA

With the advent of semiconductor process and EDA tools technology, IC designers can integrate more functions. However, to reduce the demand of time-to-market and tackle the increasing complexity of SoC, the need of fast prototyping and testing is growing. Taking advantage of deep submicron technology, modern FPGAs provide a fast and low-cost prototyping with large logic resources and high performance. So the hardware is mapped onto an emulation platform based on FPGA that mimics the behaviour of SOC. In this paper we use FPGA as a system on chip which is then used for image compression by 2-D DCT respectively and proposed SoC for image compression using soft core Microblaze. The JPEG standard defines compression techniques for image data. As a consequence, it allows to store and transfer image data with considerably reduced demand for storage space and bandwidth. From the four processes provided in the JPEG standard, only one, the baseline process is widely used. Proposed SoC for JPEG compression has been implemented on FPGA Spartan-6 SP605 evaluation board using Xilinx platform studio, because field programmable gate array have reconfigurable hardware architecture. Hence the JPEG image with high speed and reduced size can be obtained at low risk and low power consumption of about 0.699W. The proposed SoC for image compression is evaluated at 83.33MHz on Xilinx Spartan-6 FPGA.

Application of the DCT energy histogram for face recognition

In this paper, we investigate the face recognition problem via energy histogram of the DCT coefficients. Several issues related to the recognition performance are discussed, In particular the issue of histogram bin sizes and feature sets. In addition, we propose a technique for selecting the classification threshold incrementally. Experimentation was conducted on the Yale face database and results indicated that the threshold obtained via the proposed technique provides a balanced recognition in term of precision and recall. Furthermore, it demonstrated that the energy histogram algorithm outperformed the well-known Eigenface algorithm.

Adaptive depletion for improvement of MPEG video compression

Traditional data compression algorithms for 2D images work using the information theoretic paradigm, attempting to reduce redundant information by as much as possible. However, through the use of a depletion algorithm that takes advantage of characteristics of the human visual system, images can be displayed using only half or a quarter of the original information with no appreciable loss of quality.

The characteristics of the human visual system that allows the viewer to perceive a higher rate of information than is actually displayed is known as the beta or picket fence effect. It is called the picket fence effect because its effect is noticeable when a person is travelling along a picket fence. Despite the person not having an unimpeded view of the objects behind the fence at any instant, as the person is moving, the objects behind the picket fence are clearly visible. In fact, in most cases the fence is hardly noticeable at all.

The techniques we have developed uses this effect to achieve higher levels of compression than would otherwise be possible. As a fundamental characteristic of the beta effect is the requirement that there is movement of the fence in relation to the object, the beta effect can only be used in image sequences where movement between the depletion pattern and objects within the image can be achieved.

As MPEG is the recognised standard by which image sequences are coded, compatibility with MPEG is essential. We have modified our technique such that it performs in conjunction with MPEG, providing further compression over MPEG.