Fuzzy rule based multiwavelet ECG signal denoising

Since different multiwavelets, pre- and post-filters have different impulse responses and frequency responses, different multiwavelets, pre- and post-filters should be selected and applied at different noise levels for signal denoising if signals are corrupted by additive white Gaussian noises. In this paper, some fuzzy rules are formulated for integrating different multiwavelets, pre- and post-filters together so that expert knowledge on employing different multiwavelets, pre- and post-filters at different noise levels on denoising performances is exploited. When an ECG signal is received, the noise level is first estimated. Then, based on the estimated noise level and our proposed fuzzy rules, different multiwavelets, pre- and post-filters are integrated together. A hard thresholding is applied on the multiwavelet coefficients. According to extensive numerical computer simulations, our proposed fuzzy rule based multiwavelet denoising algorithm outperforms traditional multiwavelet denoising algorithms by 30%

An overview of multi-filters for eliminating impulse noise for digital images

An image through the digitization process is referred to as a digital image. The quality of the digital image may be degenerating due to interferences on the acquisition, transmission, extraction, etc. This attracted the attention of many researchers to study the causes of damage to the information in the image. In addition to finding cause of image damage, the researchers also looking for ways to overcome this problem. There are many filtering techniques that have been introduced to deal the damage to the information in the image. In addition to eliminating noise from the image, filtering techniques also aims to maintain the originality of the features in the image. Among the many research papers on image filtering there is a lack of review papers which are an important to facilitate researchers in understanding the differences in each filtering technique. Additionally, it helps researchers determine the direction of research conducted based on the results of previous research. Therefore, this paper presents a review of several filtering techniques that have been developed so far

A study of wavelet-based noise reduction techniques in mammograms

Breast cancer is one of the most common cancers and claims over one thousand lives every day. Breast cancer turns fatal only when diagnosed in late stages, but can be cured when diagnosed in its early stages. Over the last two decades, Digital Mammography has served the diagnosis of breast cancer. It is a very powerful aid for early detection of breast cancer. However, the images produced by mammography typically contain a great amount noise from the inherent characteristics of the imaging system and the radiation involved. Shot noise or quantum noise is the most significant noise which emerges as a result of uneven distribution of incident photons on the receptor. The X-ray dose given to patients must be minimized because of the risk of exposure. This noise present in mammograms manifests itself more when the dose of X-ray radiation is less and therefore needs to be treated before enhancing the mammogram for contrast and clarity. Several approaches have been taken to reduce the amount of noise in mammograms. This thesis presents a study of the wavelet-based techniques employed for noise reduction in mammograms --Abstract, page iii

A Review Paper on Video De-Interlacing Multiple Techniques

In this paper present video interlacing de-interlacing and various techniques. Focus on the different techniques of video De- Interlacing that are Intra Field, Inter Field, Motion Adaptive, Motion Compensated De- interlacing and Spatio-Temporal Interpolation. De- Interlaced video use the full resolution of each scan so produced high quality image and remove flicker problem. Techniques are work on the scan line of object Intra Field techniques use pixels of the moving object, Inter Field works on stationary regions of object, Motion Adaptive works on the edge of the Object and Motion Compensation focus video sequence and brightness variation. Advantage of using De-interlacing technique is: Better Moving object image, no flickers and high vertical resolution

An Efficient Image Denoising Approach for the Recovery of Impulse Noise

Image noise is one of the key issues in image processing applications today. The noise will affect the quality of the image and thus degrades the actual information of the image. Visual quality is the prerequisite for many imagery applications such as remote sensing. In recent years, the significance of noise assessment and the recovery of noisy images are increasing. The impulse noise is characterized by replacing a portion of an image's pixel values with random values Such noise can be introduced due to transmission errors. Accordingly, this paper focuses on the effect of visual quality of the image due to impulse noise during the transmission of images. In this paper, a hybrid statistical noise suppression technique has been developed for improving the quality of the impulse noisy color images. We further proved the performance of the proposed image enhancement scheme using the advanced performance metrics

Comparative analysis of image enhancement techniques for uterine fibroid ultrasound

Background: The Ultrasound image is a vital diagnostic tool in the preliminary clinical assessment of many diseases, especially in Obstetrics and Gynecology. However, poor ultrasound image quality often leads to the inaccurate diagnosis of diseases such as uterine fibroids. Many researchers have proposed various methods for improving ultrasound image quality. Objective: To explore by comparison of four image enhancement techniques, the best approach for the enhancement of uterine fibroid images towards achieving better diagnosis and proper management of the disease..Methodology: The study assessed and compared the performance of four (4) different image enhancement techniques namely; Contrast stretching, Gamma correction, Histogram equalization(HE) and Contrast limited adaptive histogram equalization (CLAHE) on uterine fibroid ultrasound image Twenty (20) Ultrasound images from thedatabasewere downloaded and processed in MATLAB (2015a version) using image processing toolbox. Based on histogram distribution and statistical features (Mean, Standard Deviation and Entropy), the enhanced images were evaluated and compared. Results: The results show that Contrast stretching performed better based on Histogram distribution while CLAHE shows superior performance on Statistical featuresConclusion: Contrast stretching and Contrast limited adaptive histogram equalization (CLAHE)have demostrated good performance in enhancement of uterine fibroid ultrasound ima