Digital Processing

Image fusion is a technique to improve the image quality. In this paper a new way is drawn to fuse two images by using max-min operations in Sugeno’s Intuitionistic fuzzy generator. It operates on image with lot of uncertainties. Firstly input images are reform into Intuitionistic fuzzy images (IFIs) and then evaluate fuzzy rules by using best entropy of input images, and IFIs are reconstructing based on black-count & white-count. This paper compares the performance of Average, Fuzzy Sets, Intuitionistic Fuzzy Sets and Sugeno’s type Intuitionistic fuzzy (proposed method) in terms of various performance measures.

This research work is nominated for an image protection technique in the area of spatial domain based digital watermarking and steganography. The proposed work has evolved a hybrid algorithm, Namely, MP-1. In this paper, a new data hiding and digital watermarking algorithm basedonimage matrix vectorization is provided. Experimental results show that the research work has achievedfew of targeted goal such as good concealment ability, large embedding capacity. The proposed algorithm can be widely used in area of spatial domain based digital watermarking and steganography.

Image fusion is one of the techniques in Image processing. In this paper, we are going to propose a Image fusion method based on Teaching Learning Based Optimization. Taking two multifocused images, we are going to divide them into blocks then the contrast visibility of the two image blocks then is calculated. TLBO algorithm is performed to obtain optimal coefficients and fused image is acquired finally using this Optimal Coefficients. For different set of multi focus images, different quantitative measured are calculated. Then the results of proposed method are compared with existing Particle Swarm Optimization.

This paper proposes an image hiding technique that exhibits good quality with higher embedding capacity. In this technique, both secret and cover images are divided into non overlapping blocks. The secret image is embedded into a cover image block by block using Range Normalization Technique. This technique exhibits advantages of high embedding capacity with less computational complexity. Compared with the existing algorithms, the quality of the stego and reconstructed image is found to be good.

Technologies have advanced rapidly in the field of digital signal processing due to advances made in high speed, low cost digital integrated chips. These technologies have further stimulated ever increasing use of signal representation in digital form for purposes of transmission, measurement, control and storage. Design of digital filters especially adaptive or semi adaptive is the necessity of the hour for SAR applications. The aim of this research work is to design and performance evaluation of 380-400 KHz Bartlett, Blackman and Chebyshev digital semi adaptive filters. For this work XILINX and MATLAB softwares were used for the design. As pert of practical research work these designs were translated using FPGA hardware SPARTAN-3E kit. These were optimized, analyzed, compared and evaluated keeping the sampling frequency at 5 MHz for 64 order. Both these filters designed using software and hardware were tested by passing a sinusoidal test signal of 381 KHz along with noise and the filtered output signals are presented.

Wavelet transforms enable us to represent signals with a high degree of scarcity. Wavelet thresholding is a signal estimation technique that exploits the capabilities of wavelet transform for signal denoising. The aim of this paper is to study various thresholding techniques such as Sure Shrink, Visu-Shrink and Bayes Shrink and determine the best one for image denoising. This paper presents an overview of various threshold methods for image denoising. Wavelet transform based denoising techniques are of greater interest because of their performance over Fourier and other spatial domain techniques. Selection of optimal threshold is crucial since threshold value governs the performance of denoising algorithms. Hence it is required to tune the threshold parameter for better PSNR values. In this paper, we present various wavelet based shrinkage methods for optimal threshold selection for noise removal.

Kidney stone disease is very common among Indians and approximately 5-7 million patients suffer from stone disease.The most popular imaging modality for its treatment is ultrasound imaging.Segmentation accuracy determines the eventual success or failure of computerized analysis procedures. Traditional methods available for segmentation of kidney stones are not accurate. We use the evolutionary techniques for segmentation of the kidney stone ultrasound images for the first time based on electromagnetism optimization algorithm and harmony search algorithm for determining multilevel threshold of images. In most cases, the optimal thresholds are found by the minimizing or maximizing an objective function, which depends on the positions of the thresholds. We identify a class of objective functions for which the optimal thresholds can be found using algorithms with low time complexities. The Kapur’s entropy function and Otsu’s between class variance is maximized using these algorithms and an optimal threshold values at different levels are found out. The area of extracted stone is calculated and compared with the area given by the expert radiologist. The other metric used to compare the segmented image and the original image is the peak signal to-noise-ratio (PSNR) value. The relative error is also calculated to show the segmentation accuracy of each method.

One of the most common problems in digital image restoration is motion blur caused by an image captured from a moving platform especially at low light condition having long exposure time of camera. Removing of blur is always challenging for image processing field because one has to estimate the motion blur which can spatially differ over image. Motion blur is simply an undesired effect. Restoration of blur image is very important in many of the cases like identification of number plates of moving vehicle and identification moving human beings. In restoration of motion blur the knowledge of the point spread function (PSF) is key factor. This paper presents the algorithm to estimate PSF parameters like motion blur angle and the motion blur length. Once PSF parameters are estimated then restoration of the blurred image can be achieved. Furthermore paper discusses the comparative study of different restoration techniques. The experimental result shows estimated blur angle and blur length are very close to theoretical value and the blur images with natural and artificial noise are successfully restored. The wavelet based fused image shows the best results.

Wavelet transforms enable us to represent signals with a high degree of scarcity. Wavelet thresholding is a signal estimation technique that exploits the capabilities of wavelet transform for signal denoising. The aim of this paper is to study various thresholding techniques such as Sure Shrink, Visu Shrink and Bayes Shrink and determine the best one for image denoising. This paper presents an overview of various threshold methods for image denoising. Wavelet transform based denoising techniques are of greater interest because of their performance over Fourier and other spatial domain techniques. Selection of optimal threshold is crucial since threshold value governs the performance of denoising algorithms. Hence it is required to tune the threshold parameter for better PSNR values. In this paper, we present various wavelet based shrinkage methods for optimal threshold selection for noise removal.

The present study is about Viewers Perceptions about Code of Ethics and its Applications in Political Talk Shows (A Survey Conducted at Sargodha City). Political talk shows Capital Talk (Geo News) Kal Tak (Express News) On the Front (Dunya News) Sawal Yeh Hai (ARY News) and News Beat (SAMAA TV) are selected for this study. Total two hundred respondents have been selected for data collection with the help of questionnaire from Sargodha city. Social responsibility theory (SRT) is use to check the application code of ethics of media in the society. The Social Responsibility Theory (SRT) claims that the media has a duty to public and this theoretical approach is a result of shifting media ethics. Present research is identified to find the impact of analysis and discussion by experts through politics talk shows and opportunity of media ethics. This is becoming a more and more essential issue in modern society. Do the anchorpersons of TV political talk shows have focus on social responsibility and respect for media ethics in order to satisfy the public? Empirical findings show that Geo News program Capital Talk is more frequently watched by viewers as compared to other political talk show. It is also finding that Geo News program Capital Talk provides more political awareness as compared to other political talk shows. Findings show that Javed Chudary in his political talk show (Kal Tak) followed code of ethics as compared to other anchorperson TV channels.