Abstract Planetary nebulae (PN) represents the short phase in the life of stars with masses (0.89-7) M☉. Several physical processes taking place during the red giant phase of low and intermediates-mass stars. These processes include :1) The regular (early ) wind and the envelope ejection, 2) The thermal pulses during Asymptotic Giant Branch (AGB ) phase. In this paper it is briefly discussed how such processes affect the mass range of Planetary Nebulae(PN) nuclei(core) and their evolution, and the PN life time, and fading time for the masses which adopted. The Synthetic model is adopted. The envelope mass of star (MeN ) and transition time (ttr) calculated respectively for the parameter (MeR =1.5,2, 3×10-3 M☉). Another time scale is o

Median filter is adopted to match the noise statistics of the degradation seeking good quality smoothing images. Two methods are suggested in this paper(Pentagonal-Hexagonal mask and Scan Window Mask), the study involved modified median filter for improving noise suppression, the modification is considered toward more reliable results. Modification median filter (Pentagonal-Hexagonal mask) was found gave better results (qualitatively and quantitatively ) than classical median filters and another suggested method (Scan Window Mask), but this will be on the account of the time required. But sometimes when the noise is line type the cross 3x3 filter preferred to another one Pentagonal-Hexagonal with few variation. Scan Window Mask gave bett

 Uncompressed form of the digital images are needed a very large storage capacity amount, as a consequence requires large communication bandwidth for data transmission over the network. Image compression techniques not only minimize the image storage space but also preserve the quality of image. This paper reveal image compression technique which uses distinct image coding scheme based on wavelet transform that combined effective types of compression algorithms for further compression. EZW and SPIHT algorithms are types of significant compression techniques that obtainable for lossy image compression algorithms. The EZW coding is a worthwhile and simple efficient algorithm. SPIHT is an most powerful technique that utilize for image

This paper presents a combination of enhancement techniques for fingerprint images affected by different type of noise. These techniques were applied to improve image quality and come up with an acceptable image contrast. The proposed method included five different enhancement techniques: Normalization, Histogram Equalization, Binarization, Skeletonization and Fusion. The Normalization process standardized the pixel intensity which facilitated the processing of subsequent image enhancement stages. Subsequently, the Histogram Equalization technique increased the contrast of the images. Furthermore, the Binarization and Skeletonization techniques were implemented to differentiate between the ridge and valley structures and to obtain one

      Recently, digital communication has become a critical necessity and so the Internet has become the most used medium and most efficient for digital communication. At the same time, data transmitted through the Internet are becoming more vulnerable. Therefore, the issue of maintaining secrecy of data is very important, especially if the data is personal or confidential. Steganography has provided a reliable method for solving such problems. Steganography is an effective technique in secret communication in digital worlds where data sharing and transfer is increasing through the Internet, emails and other ways. The main challenges of steganography methods are the undetectability and the imperceptibility of con

A new method presented in this work to detect the existence of hidden

data as a secret message in images. This method must be applyied only on images which have the same visible properties (similar in perspective) where the human eyes cannot detect the difference between them.

This method is based on Image Quality Metrics (Structural Contents

Metric), which means the comparison between the original images and stego images, and determines the size ofthe hidden data. We applied the method to four different images, we detect by this method the hidden data and  find exactly the same size of the hidden data.

There are many images you need to large Khoznah space With the continued evolution of storage technology for computers, there is a need nailed required to reduce Alkhoznip space for pictures and image compression in a good way, the conversion method Alamueja

     Marking content with descriptive terms that depict the image content is called “tagging,” which is a well-known method to organize content for future navigation, filtering, or searching. Manually tagging video or image content is a time-consuming and expensive process. Accordingly, the tags supplied by humans are often noisy, incomplete, subjective, and inadequate. Automatic Image Tagging can spontaneously assign semantic keywords according to the visual information of images, thereby allowing images to be retrieved, organized, and managed by tag. This paper presents a survey and analysis of the state-of-the-art approaches for the automatic tagging of video and image data. The analysis in this paper covered the publications

In all applications and specially in real time applications, image processing and compression plays in modern life a very important part in both storage and transmission over internet for example, but finding orthogonal matrices as a filter or transform in different sizes is very complex and importance to using in different applications like image processing and communications systems, at present, new method to find orthogonal matrices as transform filter then used for Mixed Transforms Generated by using a technique so-called Tensor Product based for Data Processing, these techniques are developed and utilized. Our aims at this paper are to evaluate and analyze this new mixed technique in Image Compression using the Discrete Wavelet Transfo

Abstract

 The objective of image fusion is to merge multiple sources of images together in such a way that the final representation contains higher amount of useful information than any input one.. In this paper, a weighted average fusion method is proposed. It depends on using weights that are extracted from source images using counterlet transform. The extraction method is done by making the approximated transformed coefficients equal to zero, then taking the inverse counterlet transform to get the details of the images to be fused. The performance of the proposed algorithm has been verified on several grey scale and color test  images, and compared with some present methods.