28 May 2003 Tensor form of image representation: enhancement by image-signals
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In this paper, a new method of image enhancement is introduced. The method is based on the tensor (or vectorial) representation of the two-dimensional image with respect to the Fourier transform. In this representation, the image is defined as a set of one-dimensional (1-D) image-signals that split the Fourier transform into a set of 1-D transforms. As a result, the problem of the image enhancement is reduced to the 1-D processing the splitting signals. The splitting of the image yields a simple model for the image enhancement, when by using only a few image-signals it is possible to achieve the image enhancement that is comparative to the known class of the frequency domain based parametric image enhancement algorithms, that are used widely for the object detection and visualization. A quantitative measure of image enhancement that is related to the Weber's law of the human visual system is considered. Based on the quantitative measure the best parameters for image enhancement can be found for each image-signal to be processed separately. Examples of image-signals and their contributions in process of enhancement of an image 256×256 are given.
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Artyom M. Grigoryan, Artyom M. Grigoryan, Sos S. Agaian, Sos S. Agaian, "Tensor form of image representation: enhancement by image-signals", Proc. SPIE 5014, Image Processing: Algorithms and Systems II, (28 May 2003); doi: 10.1117/12.473063; https://doi.org/10.1117/12.473063


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