The study aimed to identify the treatment of the press image of the Great Return Marches in the French international news agency AFP by knowing the most important issues, their direction and the degree of interest in them. The study belongs to the descriptive research, and used the survey method, within the context of the content analysis method, and the researcher relied on the content analysis form tool and the interview tool to collect data. The study population is represented in the photos published by the French News Agency about the Great Return Marches during the period (end of March / 2018 until the end of November / 2019. The researcher chose an intentional sample using the Complete Census method. The study material represented

A frequently used approach for denoising is the shrinkage of coefficients of the noisy signal representation in a transform domain. This paper proposes an algorithm based on hybrid transform (stationary wavelet transform proceeding by slantlet transform); The slantlet transform is applied to the approximation subband of the stationary wavelet transform. BlockShrink thresholding technique is applied to the hybrid transform coefficients. This technique can decide the optimal block size and thresholding for every wavelet subband by risk estimate (SURE). The proposed algorithm was executed by using MATLAB R2010aminimizing Stein’s unbiased with natural images contaminated by white Gaussian noise. Numerical results show that our algorithm co

The effectiveness of detecting and matching of image features using multiple views of a specified scene using dynamic scene analysis is considered to be a critical first step for many applications in computer vision image processing. The Scale invariant feature transform (SIFT) can be applied very successfully of typical images captured by a digital camera.
In this paper, firstly the SIFT and its variants are systematically analyzed. Then, the performances are evaluated in many situations: change in rotation, change in blurs, change in scale and change in illumination. The outcome results show that each algorithm has its advantages when compared with other algorithms

      In the last decade, 3D models gained interest in many applications, such as games, the medical field, and manufacture. It is necessary to protect these models from unauthorized copying, distribution, and editing. Digital watermarking is the best way to solve this problem. This paper introduces a robust watermarking method by embedding the watermark in the low-frequency domain, then selecting the coarsest level for embedding the watermark based on the strength factor. The invisibility of the watermark for the proposed algorithm is tested by using different measurements, such as HD and PSNR. The robustness was tested by using different types of attacks; the correlation coefficient was applied for the evaluati

        In this paper, new transform with fundamental properties are presented. The new transform has many interesting properties and applications which make it rival to other transforms.

Furthermore, we generalize all existing differentiation, integration, and convolution theorems in the existing literature. New results and new shifting theorems are introduced. Finally, comprehensive list of this transforms of functions will be providing.

This paper presents a proposed method for (CBIR) from using Discrete Cosine Transform with Kekre Wavelet Transform (DCT/KWT), and Daubechies Wavelet Transform with Kekre Wavelet Transform (D4/KWT) to extract features for Distributed Database system where clients/server as a Star topology, client send the query image and server (which has the database) make all the work and then send the retrieval images to the client. A comparison between these two approaches: first DCT compare with DCT/KWT and second D4 compare with D4/KWT are made. The work experimented over the image database of 200 images of 4 categories and the performance of image retrieval with respect to two similarity measures namely Euclidian distance (ED) and sum of absolute diff

conventional FCM algorithm does not fully utilize the spatial information in the image. In this research, we use a FCM algorithm that incorporates spatial information into the membership function for clustering. The spatial function is the summation of the membership functions in the neighborhood of each pixel under consideration. The advantages of the method are that it is less
sensitive to noise than other techniques, and it yields regions more homogeneous than those of other methods. This technique is a powerful method for noisy image segmentation. 

Recently digital mammography is most widely used technology for early detection of breast cancer. The main diagnosing elements such as lesion or masses in digital mammograms are with law contrast. The purpose of this paper is to enhance the mammogram images by increasing its contrast. Different enhancement method are used for this purpose such as histogram equalization (HE), Contrast Limited Adaptive Histogram Equalization (CLAHE), Morphological, and Retinex. The Retinex method also implement by combining it with HE once, and with CLAHE to improve its performance. The experimental results show that using Retinex with CLAHE can produce an image with enhancement in contrast better than using it with HE method and better than other methods