Histogram equalization

About: Histogram equalization is a research topic. Over the lifetime, 5755 publications have been published within this topic receiving 89313 citations.

Reversible image data hiding with contrast enhancement

Abstract: Reversible data hiding (RDH) continues to be intensively studied locally of signal processing. To judge the performance of the RDH formula, hiding rate and marked picture quality are essential metrics. There exists a trade-off together because growing the hiding rate frequently causes more distortion in image content. To measure the distortion, the peak signal-to-noise ratio (PSNR) value ofthemarked image is frequently calculated. The greatest two bins within the histogram are selected for data embedding to ensure that histogram equalization could be carried out by repeating the procedure. Alongside it details are to be embedded combined with the message bits into the host image so the original image is totally recoverable. The suggested formula was developed on two teams of images to demonstrate its efficiency. Within this letter, a manuscript reversible data hiding (RDH) algorithmic suggested for digital images. Rather than attempting to keep the PSNR value high, the suggested formula improves the contrast of the image to enhance its visual quality. To the best understanding, it's the first algorithm that accomplishes image contrast enhancement with data hiding. In addition, the evaluation results reveal that the visual quality could be preserved after a great deal of message bits happen to be embedded into the contrast-enhanced images, better still than three specific MATLAB functions employed for image contrast enhancement.

A Histogramm with Perceptually Smooth Color Transition for Image Retrieval.

Abstract: We propose a novel histogram generation technique using the HSV color space. The histogram retains a perceptually smooth color transition that enables us to do a window-based comparison of feature vectors for the purpose of effective retrieval of similar images from very large databases. During retrieval, we use a vector cosine distance measure for the ordering of image feature vectors. This distance measure shows an improvement in the retrieval result over the traditional Euclidean distance.

An adaptive image enhancement technique by combining cuckoo search and particle swarm optimization algorithm

Abstract: Image enhancement is an important procedure of image processing and analysis This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image The enhancement process is a nonlinear optimization problem with several constraints CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper

Feature extraction combining spectral noise reduction and cepstral histogram equalization for robust ASR.

Abstract: This work is mainly focused on showing experimental results using a combination of two methods for noise compensation which are shown to be complementary: classical spectral subtraction algorithm and histogram equalization. While spectral subtraction is focused on the reduction of the additive noise in the spectral domain, histogram equalization is applied in the cepstral domain to compensate the remaining non-linear effects associated to channel distortion and additive noise. The estimation of the noise spectrum for the spectral subtraction method relies on a new algorithm for speech / non-speech detection (SND) based on order statistics. This SND classification is also used for dropping long speech pauses. Results on Aurora 2 and Aurora 3 are reported.

Destriping MODIS Data Using Overlapping Field-of-View Method

Abstract: Multispectral sensors using array of detectors are affected by striping, an artifact that appears as a series of horizontal bright or dark periodic lines in the remotely sensed images. Nonlinearities and memory effect of detectors are the main causes of the striping problem that is not effectively corrected in the onboard or postprocessing calibration phases. In order to clear striping from images, we consider a new procedure based on detector response equalization and apply it to moderate resolution imaging spectroradiometer data from Terra and Aqua satellites. After identification of the out-of-family detectors, a least squares equalization stage is considered for calibration by using the intrinsic data redundancy caused by the bow-tie effect, where multiple observations of the same field of view are available fr.om different detectors. The main advantage of this method, with respect to others such as the histogram equalization, is due to the independence of the measurements on the scene statistics, which, otherwise, will cause an overestimation or underestimation of the detectors' responses. The new procedure performance is validated using data received at the Mediterranean Agency for Remote Sensing and environmental control ground station facility in benevento-Italy and data downloaded from NASA LAADS Web site. The main results are presented, by showing the effectiveness of the method and the stability of the correction coefficients, at least on one-orbit periods.