Retinex theory for color image enhancement: A systematic review

A short but comprehensive review of Retinex has been presented in this paper. Retinex theory aims to explain human color perception. In addition, its derivation on modifying the reflectance components has introduced effective approaches for images contrast enhancement. In this review, the classical theory of Retinex has been covered. Moreover, advance and improved techniques of Retinex, proposed in the literature, have been addressed. Strength and weakness aspects of each technique are discussed and compared. An optimum parameter is needed to be determined to define the image degradation level. Such parameter determination would help in quantifying the amount of adjustment in the Retinex theory. Thus, a robust framework to modify the reflectance component of the Retinex theory can be developed to enhance the overall quality of color images

A Retinex-based Image Enhancement Scheme with Noise Aware Shadow-up Function

This paper proposes a novel image contrast enhancement method based on both a noise aware shadow-up function and Retinex (retina and cortex) decomposition. Under low light conditions, images taken by digital cameras have low contrast in dark or bright regions. This is due to a limited dynamic range that imaging sensors have. For this reason, various contrast enhancement methods have been proposed. Our proposed method can enhance the contrast of images without not only over-enhancement but also noise amplification. In the proposed method, an image is decomposed into illumination layer and reflectance layer based on the retinex theory, and lightness information of the illumination layer is adjusted. A shadow-up function is used for preventing over-enhancement. The proposed mapping function, designed by using a noise aware histogram, allows not only to enhance contrast of dark region, but also to avoid amplifying noise, even under strong noise environments.Comment: To appear in IWAIT-IFMIA 201

Алгоритм адаптивного повышения контраста для систем распознания объектов

В статье предложен подход, позволяющий с помощью внедрения обратной связи в систему распознания объектов адаптивно регулировать степень повышения контраста. Исследовано влияние результатов внедрения на эффективность и надежность работы систем распознания объектовThere has been proposed approach that allows adjusting the level of contrast enchantment by implementing the feed back into the object recognition system. Influence of the approach implementation on the effectiveness and robustness of the recognition system was studie

Multiscale Retinex with Data-dependent Offset

As one of methods to improve the image quality, there is a method called multiscale retinex (MSR) which has been proposed by D.J. Jobson et al. In MSR, the reection components of an image are extracted and emphasized, and then the image with improved quality is obtained. This method is very useful and powerful especially for the visibility improvement of dark regions of the image. However, the resulting image tends to give us the unnatural impression because luminance components are removed, and the global contrast of the image is decreased in the processing. In this paper, a new MSR with a variable offset, which changes dependently on the local luminance information of the image, is proposed in order to overcome the disadvantage of the conventional MSR, and to further improve the image quality. Through the experiments, the effectiveness of the proposed method is illustrated

An Improved Approach for Contrast Enhancement of Spinal Cord Images based on Multiscale Retinex Algorithm

This paper presents a new approach for contrast enhancement of spinal cord medical images based on multirate scheme incorporated into multiscale retinex algorithm. The proposed work here uses HSV color space, since HSV color space separates color details from intensity. The enhancement of medical image is achieved by down sampling the original image into five versions, namely, tiny, small, medium, fine, and normal scale. This is due to the fact that the each versions of the image when independently enhanced and reconstructed results in enormous improvement in the visual quality. Further, the contrast stretching and MultiScale Retinex (MSR) techniques are exploited in order to enhance each of the scaled version of the image. Finally, the enhanced image is obtained by combining each of these scales in an efficient way to obtain the composite enhanced image. The efficiency of the proposed algorithm is validated by using a wavelet energy metric in the wavelet domain. Reconstructed image using proposed method highlights the details (edges and tissues), reduces image noise (Gaussian and Speckle) and improves the overall contrast. The proposed algorithm also enhances sharp edges of the tissue surrounding the spinal cord regions which is useful for diagnosis of spinal cord lesions. Elaborated experiments are conducted on several medical images and results presented show that the enhanced medical pictures are of good quality and is found to be better compared with other researcher methods.Comment: 13 pages, 6 figures, International Journal of Imaging and Robotics. arXiv admin note: text overlap with arXiv:1406.571

A Fuzzy Homomorphic Algorithm for Image Enhancement

The implementation and analysis of a novel Fuzzy Homomorphic image enhancement technique is presented. The technique combines the logarithmic transform with fuzzy membership functions to deliver an intuitive method of image enhancement. This algorithm reduces the computational complexity by eliminating the need for image-size-dependent filter kernels and the forward and inverse Fourier Transforms.   The proposed algorithm is compared with the more established algorithms for the enhancement of low contrast images with uneven illumination. The results show that the fuzzy method provides similar or better results than the frequency domain method and some other well-known image enhancement algorithms