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We propose a new framework for evaluating image enhancement methods. In this work, we focus on contrast enhancement, and use the joint probability and the mutual information derived from the image co-occurrence matrix to determine the proposed index. We show that the second order entropy and the mutual information can be used jointly for tracking and evaluating the effect of contrast enhancement....
Contrast enhancement is one of the most studied problems in image processing. A plethora of approaches has been proposed in the literature for image enhancement since the pioneer work of Kovasznay and Joseph in 1955 [1] and the famous contribution of Gabor in 1965 on image deblurring [2]. However, very few works have been dedicated to contrast enhancement evaluation. This is mainly due to the fact...
The development of robust No-Reference Image Quality Assessment (NR-IQA) techniques continues to be a challenging problem. NR-IQA techniques are critical In numerous multimedia applications. Most existing techniques are distortion-specific, as they are only efficient when the type of distortion is known. In this work, we introduce a computationally efficient NR-IQA algorithm that uses basic filtering...
With the advent of powerful image editing tools, manipulating images and changing their content is becoming a trivial task. It is now possible to add, modify, or remove important features from an image without leaving any perceptual traces of tampering. With more than several million pictures uploaded daily to the net, and the introduction of e-Government services, it is becoming important to develop...
In this research paper a conventional and a power split hybrid vehicle drive train are simulated and modeled in Autonomie for comparative analysis between the two motioned types of vehicles. For this purpose both types of vehicles are analyzed for two different types of cycles, namely, UDDS Cycle and HWFET cycle. The initial results of the analysis clearly shows that the fuel is used more efficiently...
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