A Novel Directional Weighted Minimum Deviation (DWMD) Based Filter for Removal of Random Valued Impulse Noise

The most median-based de noising methods works fine for restoring the images corrupted by Randomn Valued Impulse Noise with low noise level but very poor with highly corrupted images. In this paper a directional weighted minimum deviation (DWMD) based filter has been proposed for removal of high random valued impulse noise (RVIN). The proposed approach based on Standard Deviation (SD) works in two phases. The first phase detects the contaminated pixels by differencing between the test pixel and its neighbor pixels aligned with four main directions. The second phase filters only those pixels keeping others intact. The filtering scheme is based on minimum standard deviation of the four directional pixels. Extensive simulations show that the proposed filter not only provide better performance of de noising RVIN but can preserve more details features even thin lines or dots. This technique shows better performance in terms of PSNR, Image Fidelity and Computational Cost compared to the existing filters.

Self Authentication of image through Daubechies Transform technique (SADT)

In this paper a 4 x 4 Daubechies transform based authentication technique termed as SADT has been proposed to authenticate gray scale images. The cover image is transformed into the frequency domain using 4 x 4 mask in a row major order using Daubechies transform technique, resulting four frequency subbands AF, HF, VF and DF. One byte of every band in a mask is embedding with two or four bits of secret information. Experimental results are computed and compared with the existing authentication techniques like Li s method [5], SCDFT [6], Region-Based method [7] and other similar techniques based on Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and Image Fidelity (IF), which shows better performance in SADT.

Secured Wireless Communication using Fuzzy Logic based High Speed Public-Key Cryptography (FLHSPKC)

In this paper secured wireless communication using fuzzy logic based high speed public key cryptography (FLHSPKC) has been proposed by satisfying the major issues likes computational safety, power management and restricted usage of memory in wireless communication. Wireless Sensor Network (WSN) has several major constraints likes inadequate source of energy, restricted computational potentiality and limited memory. Though conventional Elliptic Curve Cryptography (ECC) which is a sort of public key cryptography used in wireless communication provides equivalent level of security like other existing public key algorithm using smaller parameters than other but this traditional ECC does not take care of all these major limitations in WSN. In conventional ECC consider Elliptic curve point p, an arbitrary integer k and modulus m, ECC carry out scalar multiplication kP mod m, which takes about 80% of key computation time on WSN. In this paper proposed FLHSPKC scheme provides some novel strategy including novel soft computing based strategy to speed up scalar multiplication in conventional ECC and which in turn takes shorter computational time and also satisfies power consumption restraint, limited usage of memory without hampering the security level. Performance analysis of the different strategies under FLHSPKC scheme and comparison study with existing conventional ECC methods has been done.

Energy Efficient Wireless Communication using Genetic Algorithm Guided Faster Light Weight Digital Signature Algorithm (GADSA)

In this paper GA based light weight faster version of Digital Signature Algorithm (GADSA) in wireless communication has been proposed. Various genetic operators like crossover and mutation are used to optimizing amount of modular multiplication. Roulette Wheel selection mechanism helps to select best chromosome which in turn helps in faster computation and minimizes the time requirements for DSA. Minimization of number of modular multiplication itself a NP-hard problem that means there is no polynomial time deterministic algorithm for this purpose. This paper deals with this problem using GA based optimization algorithm for minimization of the modular multiplication. Proposed GADSA initiates with an initial population comprises of set of valid and complete set of individuals. Some operators are used to generate feasible valid offspring from the existing one. Among several exponents the best solution reached by GADSA is compared with some of the existing techniques. Extensive simulations shows competitive results for the proposed GADSA.

Image Filtering using All Neighbor Directional Weighted Pixels: Optimization using Particle Swarm Optimization

In this paper a novel approach for de noising images corrupted by random valued impulses has been proposed. Noise suppression is done in two steps. The detection of noisy pixels is done using all neighbor directional weighted pixels (ANDWP) in the 5 x 5 window. The filtering scheme is based on minimum variance of the four directional pixels. In this approach, relatively recent category of stochastic global optimization technique i.e., particle swarm optimization (PSO) has also been used for searching the parameters of detection and filtering operators required for optimal performance. Results obtained shows better de noising and preservation of fine details for highly corrupted images.