Display devices play image files, of which contrast enhancement methods are usually employed to bring out visual details to achieve better visual quality. However, applied to high resolution images, the contrast enhancement method entails high computation costs mostly due to histogram computations. Therefore, this letter proposes a parallel histogram calculation algorithm using the column histograms and difference histograms to reduce histogram computations. Experimental results show that the proposed algorithm is effective for histogram-based image contrast enhancement.

In this letter, a design of inverse discrete cosine transform for energy-efficient watermarking mechanism based on DS-CDMA with significant energy and area reduction is presented. Taking advantage of converged input data value set as a precomputation concept, the proposed one-dimensional IDCT is a multiplierless hardware which differs from Loeffler architecture and has benefits of low complexity and low power consumption. The experimental results show that our design can reduce 85.2% energy consumption and 58.6% area. Various spectrum and spatial attacks are also tested to corroborate the robustness.

The use of image contrast enhancement has become increasingly essential due to the need to better show the visual information contained within the image for all vision-based systems. This has lead to motivation for the design of a powerful and accurate automatic contrast enhancement for a digital image. Histogram equalization is the most commonly used contrast enhancement method. However, the conventional histogram equalization methods usually result in excessive contrast enhancement, which causes the unnatural look and visual artifacts of the processed image. In this paper, we propose a novel histogram equalization method using the automatic histogram separation along with the piecewise transformed function. The contrast enhancement results of the proposed method were not only analyzed through qualitative visual inspection and for quantitative accuracy, but are also compared to the results of other state-of-the-art methods.

The Towers of Hanoi problem is a classical problem in puzzles, games, mathematics, data structures, and algorithms. In this letter, a least memory used algorithm is proposed by combining the source array and target array for comparing the sizes of disk and labeling the disks in the towers of Hanoi problem. As a result, the proposed algorithm reduces the space needed from 2n+2 to n+5, where n represents the disks number.

A histogram is a common graphical descriptor to represent features of distribution of pixels in an image. However, for most of the applications that apply histograms, the time complexity of histogram construction is much higher than that of the other parts of the applications. Hence, column histograms had been presented to construct the local histogram in constant time. In order to increase its performance, this letter proposes a linked-list histogram to avoid generating empty bins, further using hash tables with bin entries to map pixels. Experimental results demonstrate the effectiveness of the proposed method and its superiority to the state-of-the-art method.

In this letter, we propose a novel motion detection method in order to accurately perform the detection of moving objects in the automatic video surveillance system. Based on the proposed Background Generation Mechanism, the presence of either moving object or background information is firstly checked in order to supply the selective updating of the high-quality adaptive background model, which facilitates the further motion detection using the Laplacian distribution model. The overall results of the detection accuracy will be demonstrated that our proposed method attains a substantially higher degree of efficacy, outperforming the state-of-the-art method by average Similarity accuracy rates of up to 56.64%, 27.78%, 50.04%, 43.33%, and 44.09%, respectively.