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As a field image enhancement has evolved due to an inherent human want for better image quality. Traditional methods apply linear scaling functions operating on image attributes such as contrast and brightness whereas it is often necessary to amplify specific localized elements as edges in images. This need has resulted in a search for better methods in efforts to boost these local characters in as much as the general image is concerned. Thus, this paper aims to propose an edge- and texture-aware image enhancement framework based on full-depth Gabor filters and morphological operation that can overcome the above drawbacks and gain the desired image texture complexities and brightness. Hence the method proposed in this work aims at preserving edge and texture at the same time to get an image that looks natural and has improved aesthetics. This bank of filters is mostly useful to obtain small details of texture and sharpness. An inverse gamma transform is then applied to the image to reduce gamma distortions in the image, while another process known as depth-of-defocus is to determine the edges of the texture image. These are the detected edges used in the coarse refinement stage. Morphological operations are employed to populate and repaint the elaborate structures of this image to fit up. An experimental analysis of the proposed method is carried out by conducting experiments on several structures of images including images with different textured content, different levels of brightness, and noise. This result is generalized with the help of quantitative measures and qualitative analysis on PSNR, SSIM, FSIM, and GMSD parameters.

The use of computers today is the most important and widespread means of storing, retrieving and circulating information through local and international networks and smart phones. Thus it is possible to intercept information through different networks or access to computers, whether independent or connected with the network for the purpose of viewing its contents or stealing information or to tamper with, and in this light must ensure the protection, reliability and credibility of information and preservation of the emergence of various means of protection such as the use of encryption and techniques of hiding or coverage of information. This research is based on a hybrid method between the Discrete Wavelets Translate technique (DWT) and the Chaos system based on the Least Significant Bit algorithm (LSB) to encrypt and hide a digital video file within another digital video that represents the cover by inserting the digital video file and segmenting it into a set of frames and then analyze each frame to its colors (red, green and blue) and then study the color values ​​of each frame and the process of encryption based on the equation of the logistics function (chaotic functions), and the application of the Discrete Wavelets Translate technique on the color slides of the cover frame. The hiding process is done using the Least Significant Bit algorithm based on the logistic function by calculating the series of random locations of cover area. The results showed that the hybridization of the Discrete Wavelets Translate technique and the chaos system based on the Least Significant Bit algorithm was an effective method for encrypting and hiding digital video files. After applying the work algorithms to a set of samples, the results showed consistency and compatibility in the encrypting and hiding process with the samples that was dealt with.

The development of data transfer technologies over multimedia or communications networks needs to be addressed to large storage units so that they can be sent and received in a packaged manner. It also takes a lot of time to transmit them while the current technologies are high standards, which reduces storage space and thus reduces transmission time and reception. The aim of the study is to compress digital video files using SVD by inserting digital video and then analyzing it into a set of frames and then processing each frame using the compression algorithm used in the research. A set of measures were used to measure the quality of the compression. The results showed that the use of a single value analysis technique was an effective method for compressing digital video files. After applying the work algorithms to a set of samples, the results also showed consistency and compatibility in the compression process with the samples that were treated.

This research aims to build a computer network system that works on detecting and locating flame by using fractal geometry in the digital video through building the network system in a server-client structure through which the characteristics of both the server and the clients are determined. A terminal stations were adapted to receive the digital video, and then divided into set of frames to be treated later on individually using fractal geometry (2 dimension variation algorithm to create fractal dimensions matrix). Studying and analyzing the value of the fractal dimensions of each frame, to identify the flame region by recognizing the common properties. Applying the suggested algorithm on Various samples exceeding 300 colored digital images containing flames with different spectra have been selected. Those images are taken by digital cameras or downloaded from the internet. On the other hand, the application on digital video applied and exceed 100 sample. Results show that using fractal dimension is an active and encouraging way in determining the characteristics of flame with its all spectra. No any negative evidence was recorded on all samples which exceed 100 sample from the digital video during the interval of the application test. Results also show the harmony and consistency in transferring process through the protocols that have been dealt with.