Histogram Equalization (HE) has been an essential addition to the Image Enhancement world. Enhancement techniques like Classical Histogram Equalization(CHE),Adaptive Histogram Equalization (AHE), Bi-Histogram Equalization (BHE) and Recursive Mean Separate Histogram Equalization (RMSHE) methods enhance contrast, brightness is not well preserved, which gives an unpleasant look to the final image ...

In this article, scale and orientation invariant object detection is performed by matching intensity level histograms. Unlike other global measurement methods, the present one uses a local feature description that allows small changes in the histogram signature, giving robustness to partial occlusions. Local features over the object histogram are extracted during a Boosting learning phase, sele...

Histogram techniques have been used in many commercial database management systems to estimate a query result size. Recently, it has been shown that they are very effective to support approximation of query processing especially aggregates. In this paper, we investigate the problem of minimizing average errors of approximate aggregates using histogram techniques. Firstly, we present a novel lin...

From the 90's, the image information retrieval methods have been on progress. As good examples of the methods, Conventional histogram method and merged-color histogram method were introduced. They could get good result in image retrieval. However, Conventional histogram method has disadvantages if the histogram is shifted as a result of intensity change. Merged-color histogram, also, causes mor...

Based on a local spatial/frequency representation,we employ a spectral histogram as a feature statistic for texture classification. The spectral histogram consists of marginal distributions of responses of a bank of filters and encodes implicitly the local structure of images through the filtering stage and the global appearance through the histogram stage. The distance between two spectral his...

Kernel based−methods using color histogram approach are recently used for visual tracking due to their efficiency and robustness. However, a color histogram suffers from the inability to encode spatial image information, thus images with very different appearances can have similar color histograms. This problem is especially critical in various applications such as retrieval for image and video...

Integral histogram image can gather speed the computing process of feature algorithm in computer vision, butex habits high working out complexity and incompetent memory access. In this paper, we propose a configurable parallel architecture to improve the computing efficiency of integral histogram. The design in the several integral objects is well supported for an integral histogram image such ...

A conventional color histogram (CCH) considers neither the color similarity across different bins nor the color dissimilarity in the same bin. Therefore, it is sensitive to noisy interference such as illumination changes and quantization errors. Furthermore, CCHs large dimension or histogram bins requires large computation on histogram comparison. To address these concerns, this paper presents ...

Histograms are the basis for numerous spatial domain image processing techniques. Histogram manipulation can be used effectively for image enhancement. In addition to providing image statistics, the information inherent in the histogram is also quiet useful in other image processing applications, such as image compression and segmentation. Histograms are simple in manipulation as well as econom...

In this paper a new desired histogram method is proposed to enhance the contrast of bimodal SAR images using histogram specification with Gamma distribution. The method is aimed to estimate the statistical parameters of the original histogram as the means and prior probabilities of the two modes using the Maximum Likelihood Gamma Distribution technique (ML). Next, we separate the two modes by s...