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An Optimal Fuzzy System for Color Image Enhancement

An Optimal Fuzzy System for Color Image Enhancement,10.1109/TIP.2006.877499,IEEE Transactions on Image Processing,Madasu Hanmandlu,Devendra Jha

An Optimal Fuzzy System for Color Image Enhancement   (Citations: 15)
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A Gaussian membership function is proposed to fuzzify the image information in spatial domain. We introduce a global contrast intensification operator (GINT), which contains three parameters, viz., intensification parameter , fuzzifier , and the crossover point , for enhancement of color images. We define fuzzy contrast-based quality factor and entropy-based quality factor and the corresponding visual factors for the desired appearance of images. By minimizing the fuzzy entropy of the image information with respect to these quality factors, the parameters , , and are calculated globally. By using the proposed technique, a visible improvement in the image quality is observed for under exposed images, as the entropy of the output image is decreased. The terminating criterion is decided by both the visual and quality factors. For over exposed and under plus over exposed images, the proposed fuzzification function needs to be modified by taking maximum intensity as the fourth parameter. The type of the images is indicated by the visual factor which is less than 1 for under exposed images and more than 1 for over exposed images.
Journal: IEEE Transactions on Image Processing , vol. 15, no. 10, pp. 2956-2966, 2006
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    • ...While Hanmandlu et al. [23] have proposed a new intensification operator, NINT, which is a parametric sigmoid function for the modification of the Gaussian type of membership on the basis of optimization of entropy by a parameter involved in the intensification operator which is suitable for gray level images; Hanmandlu and Jha [13] proposed a Gaussian membership function to fuzzify the image information in spatial domain by introducing a ...
    • ...Hanmandlu and Jha [13] calculated the global contrast intensification operator parameters t, fh, and μc globally by minimizing fuzzy entropy of the image information with respect to the quality factors...
    • ...Fig. 2 Flow chart of fuzzy logic method, after [13]...
    • ...The fuzzy logic method proposed by Hanmandlu and Jha [13] for contrast enhancement is presented in Fig. 2...
    • ...Lakshmanan et al. [26] made an inter-comparison of the various variants of the histogram-based GLG methods and the fuzzy logic method of Hanmandlu and Jha [13] to know whether any one specific algorithm can be used for automatic contrast enhancement of images from a wide variety of sensors and therefore evaluated the results of the analysis on three different images in order to ascertain which of the algorithms are better suited across a ...
    • ...Logic method after Hanmandlu and Jha [13] Bright...
    • ...The modification is that, unlike the iteratively determined values of t, fh andμc as suggested by Hanmandlu and Jha [13], we determine an optimal μc by considering the maximum of the resultant Tenengrad values and utilize the same for improving the image quality...
    • ...b–f The enhanced images of Mineral Image after applying the histogram equalization, adaptive histogram equalization with exponential distribution, GLG, fuzzy method [13] (with optimal μc = 0.32) and the modified fuzzy methods (with optimal μc = 0.36), respectively...
    • ...As can be seen from the Tenengrad values the visual quality is best for the modified fuzzy-based method with an improvement of 22% as compared to the fuzzy method of [13], and 5% as compared to the FGLG method...
    • ...An inter comparison of the conventional histogram-based contrast enhancement techniques (like HE, adaptive HE) along with the recent histogram-based GLG method (after [12]), the Fuzzy Logic method (after [13]) and the modified fuzzy logic method as suggested in this paper was carried out to ascertain which of these methods is better suited for automatic contrast enhancement of satellite images of the ocean...

    Madhu S. Nairet al. Fuzzy logic-based automatic contrast enhancement of satellite images o...

    • ...The generalized intensification (GINT) operator for enhancement in the fuzzy domain is introduced by Hanmandlu et al. [16], whose parameters are found by optimizing the image entropy.This approach works well for the underexposed images but fails if there are overexposed regions...
    • ...They are fuzzified by a modified Gaussian membership function definedin [16] as,...
    • ...wherex indicates the intensity level of the underexposed region in the range [0, a-1], xmax is the maximum intensity level and xavg is the average intensity level in the image, fh is called fuzzifier and its initial value is found from[16]:...

    Om Prakash Vermaet al. High Dynamic Range Fuzzy Color Image Enhancement

    • ...Hanmandlu and Jha [16] use a global contrast intensification (GINT) operator, which is an extended NINT operator for the enhancement of the luminance part in the fuzzy domain, and also propose the quality factors...
    • ...In this paper, we extend the approach in [16] for automatic enhancement of all types of degraded color images...
    • ...An image can be split up into underexposed and overexposed regions by using the value a. A modified Gaussian MF defined in [16] is used to fuzzify the underexposed region of the image as follows:...
    • ...A parametric sigmoid function in [16] (or simply a sigmoid operator) for enhancing the MF values of the original gray levels of the underexposed region is given by...

    Madasu Hanmandluet al. A Novel Optimal Fuzzy System for Color Image Enhancement Using Bacteri...

    • ...Thus, the fuzzy contrast [13] is written as :...
    • ...The fuzzy average contrast is defined as [13]:...

    Roli Bansalet al. Fingerprint Image Enhancement Using Type2 Fuzzy Sets

    • ...Madasu Hanmandlu used Optimal Fuzzy System[4] to enhance color image; G.Louverdis et.al.[5] used vectorordering scheme fuzzy model to process color images morphologically...

    Chen Yueet al. A Segmentation Algorithm on Color Images Using Extenics Theory

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