------------------------------------------------------------ABSTRACT--------------------------------------------------------Digital Remote Image (DRI) denoising using thresholding methods means find appropriate value (threshold) which separates noise values to actual image values without affecting the significant features of the image. The aim of this project is to develop a best poisson noise ...

A multi-stage approach is presented for thresholding document images, along with its application. The proposed method is based on two stages. Global thresholding is used in first stage to give a preliminary result. A second stage then refines the threshold value based on local spatial characteristics of the regions formed in the first stage. It automatically customizes the thresholding of regio...

This paper introduces a technique of bivariate thresholding based dual tree complex Wavelet transform(DTCWT) to remove additive and multiplicative both the noise signals. Since both the noises are different in nature hence it is difficult to remove both the noises by using single filter. Therefore two different filters are required denoise medical images which are corrupted by either of the noi...

This article shows that when the nonzero coefficients of the population correlation matrix are all greater in absolute value than (C1 log p/n) 1/2 for some constant C1, we can obtain covariance selection consistency by thresholding the sample correlation matrix. Furthermore, the rate (log p/n) is shown to be optimal.

The objective of image segmentation is to extract meaningful objects. A meaningful segmentation selects the proper threshold values to optimize a criterion using entropy. The conventional multilevel thresholding methods are efficient for bi-level thresholding. However, they are computationally expensive when extended to multilevel thresholding since they exhaustively search the optimal threshol...

An adaptive local thresholding method for microscope based high content analysis (HCA) is proposed. Cell micrographs of HCA contain detailed objects both in and out of focus, which cannot be correctly segmented by global thresholding methods. The proposed method utilizes adaptive local neighborhood size and double thresholding, and is able to produce segmentations that conform closely to percep...

In this paper, we propose a new speech enhancement system using the wavelet thresholding algorithm. The basic wavelet thresholding algorithm has some defects including the assumption of white Gaussian noise (WGN), malfunction in unvoiced segments, bad auditory quality, etc. In the proposed system, we introduce a new algorithmwhich does not require any voiced/ unvoiced detection system.Also, in ...

Denoising the CT images removes noise from the CT images and so makes the disease diagnosis procedure more efficient. The denoised images have a notable level of raise in its PSNR values, ensuring a smoother image for diagnosis purpose. In the previous work, a CT image denoising technique using window-based Multi-wavelet transformation and thresholding has been proposed. The performance of the ...

Background estimation algorithms are important in UAV (Unmanned Aerial Vehicle) vision tracking systems. Incorrect selection of an algorithm and its parameters leads to false detections that must be filtered by the objects, even if there is only one within visibility range. This paper shows that, with use genetic optimization, it possible select automatically. (CNT (CouNT), GMG (Godbehere-Matsu...

Most of the methods for video summarisation rely on complicated clustering algorithms that make them too computationally complex for real time applications. This paper presents an efficient approach for video summary generation that does not relay on complex clustering algorithms and does not require frame length as a parameter. The present scheme combines colour histogram and edge histogram fe...