In this paper, a method is proposed to automatically select reference image in HISTOGRAM MATCHING. HISTOGRAM MATCHING is one of the simplest spatial image enhancement methods which improves contrast of the initial image based on HISTOGRAM of the reference image. In the conventional HISTOGRAM MATCHING methods, user should perform several experiments on various images to find a suitable reference image. This paper presents a new method to automatically select the reference image. In this method, images are converted from RGB to HSV, and the illumination (V) components are considered to select the reference image. The appropriate reference image is selected using a similarity measure via measuring the similarity between the HISTOGRAMs of the initial image and HISTOGRAMs of the images in the data base. Indeed, an image with similar HISTOGRAM to the HISTOGRAM of the original images is more appropriate to choose as the reference image for HISTOGRAM MATCHING. Results in this research indicate superiority of the proposed approach, compared to other existing approaches, in image enhancement via HISTOGRAM MATCHING. In addition, the user would have no concern in selecting an appropriate reference image for HISTOGRAM MATCHING in the proposed approach. This approach is applicable to both RGB and gray scale images.

In digital color imaging, it is of interest to transform the color scene of an image to the other. Some attempts have been done in this case using, for example, lab color space, principal component analysis and recently HISTOGRAM rescaling method. In this research, a novel method is proposed based on the Resenfeld and Kak HISTOGRAM MATCHING algorithm. It is suggested that to transform the color scene between two images, the HISTOGRAMs of the three R, G and B channels of the input image would be matched to the corresponding HISTOGRAMs of the destination one. The performance of the introduced method was investigated for several images. The obtained results indicated that this method is well capable of transforming the color scene between images.

Estimate the position of moving objects tracking is an important and Many algorithms have been proposed. In this paper, a method to estimate the position of moving objects by solving the Bayesian equations of nonlinear systems with non-Gaussian distributed algorithm based on particle filter are offered. In this way will build the first target model of weighted HISTOGRAM, Then applying random noise in the location of the first frame image, predicted the candidate particles in the next step and build a HISTOGRAM weighted by the candidate particles and particles Start by Bhattacharya distance weighting on the similarity between the target model and candidate model particles and estimated the target position in the next frame by the resampling algorithm in the particle filter, Finally an adaptive target model update is performed, if necessary, based on the best model for particle similar to the target.

At present, applying the acoustic approaches and equipments has been increasingly used for gathering information from seafloor to produce maps with numerous applications. Multi-beam echo-sounder (MBES) is an acoustic system that measures both the depth and the backscatter strength, simultaneously. Such systems transmit a series of beams to the seafloor and receive their backscatter strengths (BS). They can be described as a function of the incident angle based on the Lambert law. Seafloor sediment classification is an important application of these data. In different studies, angular dependence has been used for this purpose. A complication occurs when the sediment types change along the swath, because it is difficult to separate from the beam angular dependence and the true backscatter strength variations. Therefore, these data should become independence of the angle. In this paper, two statistical methods based on the HISTOGRAM MATCHING are compared for removing the angular dependence: 1) HISTOGRAM MATCHING using the statistical moments, and 2) HISTOGRAM MATCHING using the image processing technique. These methods will register the BS data of large grazing angles (close to nadir) to the reference low grazing angle. Finally we will apply the two methods to a MBES data set of the Waal river, the Netherlands and compare the results.

Radiography is known as one of the oldest and most widely used nondestructive testing (NDT) techniques, where it introduces the most appreciated technique by producing images which are acting as unique fingerprint records of samples of interest. Among the interesting applications of radiography are archeological and art applications. In this research, radiography was implemented for identification of a damaged art-historical material. The sample was a brass plate belonging to Iran cultural heritage. The estimated age of the plate was about 3500 years. The plate was discovered in Lorestan province, where it is generally called “Lorestan bronze”. The plate was damaged seriously due to serious corrosion enviromental attacks, and recognition of the sample was considered as the major problem. The simple radiography method was quite helpful for the plate determination but the method suffered from some major drawbacks due to contrast and thickness measurements. The thickness measurement and corrosion/erosion evaluation were the vital components of the inspection. The image processing techniques and precise thickness measurement method were added to the digitized radiographs. For the digital image processing, a HISTOGRAM MATCHING algorithm and an edge detection method were used. After all, the resulted image showed an enhanced quality image of the original traces of the hammered design. The results showed that a good experimental setup of radiography along with the image processing technique can give a high quality radiographic image which is able to be used effectively for the identification of art antiques. The human evaluation results also confirmed the ability of the proposed method with a high degree of certainty.

The traditional method for studying non-stationary signals is spectrogram based on the short-time Fourier transform (STFT). The well known limitation of the STFT is the inherent trade-off between time and frequency resolution. The Wigner-Ville (WV) distribution has the best time-frequency resolution, but its draw back is generating cross-terms. The MATCHING pursuit (MP) distribution based on using the Gaussian atom is always positive, does not include crossterm, and has convenient resolution. In this paper, we have shown in addition to the known properties, the MP distribution can also remove the additive noise inherently. On the other words, we are able to remove the noise just by limiting the algorithm iterations and without paying any additional cost. Although the MP distribution based on using the Gaussian atoms is always positive and it has convenient resolution, according to the MP the time marginal and the frequency marginal will not be obtained accurately. In this paper, it has been shown that by implementing the minimum cross entropy (MCE) technique according to the MP distribution as a priory positive distribution, the new extracted distribution has the most similarity to the MP distribution and it also satisfies the correct time and frequency marginal.

This paper proposes an approach to improving color images su ering from low dynamic range by employing both HISTOGRAM MATCHING and HISTOGRAM stretching techniques. In the  rst stage, the color image was transformed from RGB into HSV color space, in which the color information was separated from intensity. Then, an appropriate reference image was selected by comparing component V of the enhanced image with component V of the database images using a similarity measure. The selected image was used as the target image in HISTOGRAM MATCHING algorithm for enhancement. In the second stage, components V and S were linearly stretched in order to recover the image color information. Finally, using the treated V and S components and untreated component of H, the enhanced image was obtained in RGB color space by inverse transform. The qualitative and quantitative results showed that the contrast and color of the resultant image were greatly improved using the proposed method, which outperformed the current state-of-the-art methods.

< p >The various subject matters of jurisprudence (Fiqh) contain many religious laws limited by legal measures. In these cases, the correct recognition of the fulfillment of legal measure and the way it is performed by religiously competent person is an important matter. Four theories can be driven from the expressions of the jurists in this regard including rational precision, customary precision, customary negligence and statement in detail. When it is the matter of limitation, the customary precision is the criterion for recognition of duty, but considering the way of its performance the customary accuracy is acceptable. In addition, considering the recognition of the concept of measure, the customary negligence is considered to be harmless, but considering adapting an example to the concepts, it is not acceptable. Alongside these matters, scientific and experimental precision can also be studied. While quoting and criticizing the statements, this article prefers the statement in detail. In most cases, there is a deliberation and insistence on strict observance of the specified limits in the word of divine law which indicates the importance of a particular amount in the view of the Legislator and the tolerance thereof is rejected. However, in some cases, the method of confinement may be discovered from the language of reason or other evidences and that the substantiation of a particular amount is the detector of the actual realization of the subject of religious law. Therefore, in those cases, accuracy is not demanded.