Image Fusion is being used to gather important data from such an input image array and to place it in a single output picture to make it much more meaningful & usable than either of the input images. Image fusion boosts the quality and application of data. The accuracy of the image that has fused depending on the application. It is widely used in smart robotics, audio camera fusion, photonics, system control and output, construction and inspection of electronic circuits, complex computer, software diagnostics, also smart line assembling robots. In this paper provides a literature review of different image fusion techniques in the spatial domain and frequency domain, such as averaging, min-max, block substitution, Intensity-Hue-Saturation(IHS), Principal Component Analysis (PCA), pyramid-based techniques, and transforming. Different quality metrics for quantitative analysis of these approaches have been debated.
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تعد مجالات الصورة وعلاماتها الحركية حضوراً دلالياً للاتصال العلامي واتساعاً في الرابطة الجدلية ما بين الدوال ومداليها، التي تقوم بها الرؤية الاخراجية لإنتاج دلالات اخفائية تمتلك جوهرها الانتقالي عبر الافكار بوصفها معطيات العرض، ويسعى التشفير الصوري الى بث ثنائية المعنى داخل الحقول المتعددة للعرض المسرحي، ولفهم المعنى المنبثق من هذه التشفيرات البصرية، تولدت الحاجة لبحث تشكيل هذه التشفيرات وكيفية تح
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WA Shukur, FA Abdullatif, Ibn Al-Haitham Journal For Pure and Applied Sciences, 2011 With wide spread of internet, and increase the price of information, steganography become very important to communication. Over many years used different types of digital cover to hide information as a cover channel, image from important digital cover used in steganography because widely use in internet without suspicious.
With the continuous progress of image retrieval technology, the speed of searching for the required image from a large amount of image data has become an important issue. Convolutional neural networks (CNNs) have been used in image retrieval. However, many image retrieval systems based on CNNs have poor ability to express image features. Content-based Image Retrieval (CBIR) is a method of finding desired images from image databases. However, CBIR suffers from lower accuracy in retrieving images from large-scale image databases. In this paper, the proposed system is an improvement of the convolutional neural network for greater accuracy and a machine learning tool that can be used for automatic image retrieval. It includes two phases
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The study discusses the marketing profile of electoral candidates and politicians especially the image that takes root in the minds of voters has become more important than the ideologies in the technological era or their party affiliations and voters are no longer paying attention to the concepts of a liberal, conservative, right-wing or secular, etc. while their interests have increased towards candidates. The consultants and image experts are able to make a dramatic shift in their electoral roles. They, as specialists in the electoral arena, dominate the roles of political parties.
The importance of the study comes from the fact that the image exceeds its normal framework in our contemporary world to become political and cultural