The recent technological advances in remote sensing (e.g., unmanned aerial vehicles, digital image acquisition, etc.) have vastly improved the applicability of velocimetry hydrological studies. Thus, has become an established technique with acceptable error for practical applications (the can be lower than 10%). main source errors been attributed to incomplete intrinsic and extrinsic camera cal...

In medical imaging, low signal-to-noise ratio (SNR) and/or contrast-to-noise ratio (CNR) often cause many image processing algorithms to perform poorly. Postacquisition image filtering is an important off-line image processing approach widely employed to enhance the SNR and CNR. A major drawback of many filtering techniques is image degradation by diffusing/blurring edges and/or fine structures...

By considering the features of the airport runway image filtering, an improved bilateral filtering method was proposed which can remove noise with edge preserving. Firstly the steerable filtering decomposition is used to calculate the sub-band parameters of 4 orients, and the texture feature matrix is then obtained from the sub-band local median energy. The texture similar, the spatial closer a...

The use of image denoising techniques is an important part of many medical imaging applications. One common application is to improve the image quality of low-dose (noisy) computed tomography (CT) data. While 3D image denoising previously has been applied to several volumes independently, there has not been much work done on true 4D image denoising, where the algorithm considers several volumes...

In digital image processing, filtering tasks are typically implemented using filtering masks of very small sizes, for instance, 3x3, 5x5, or 7x7. The choice of filtering coefficients are usually heuristic, without rigorous mathematical derivation. In this work, we propose a constrained least-squared (LS) error approach to design 5x5 image filtering masks, which have moderate degrees of freedom....

The key to medical image denoising technique is to remove the noise while preserving important features. Non-local mean filtering and bilateral filtering are commonly used procedures for medical image denoising. In this paper analysis and comparison of spatial as well as frequency domain methods including bilateral filtering , non-local mean filtering, wavelet thresholding, contourlet threshold...

We present an approach for modeling and filtering digitally scanned images. The digital contour of an image is segmented to identify the linear segments, the nonlinear segments and critical corners. The nonlinear segments are modeled by B-splines. To remove the contour noise, we propose a weighted least q m s model to account for both the fitness of the splines as well as their approximate cur...

In many autonomous mobile applications, robots must be capable of analyzing motion of moving objects in their environment. Duringmovement of robot the quality of images is affected by quakes of camera which cause high errors in image processing outputs. In thispaper, we propose a novel method to effectively overcome this problem using Neural Networks and Kalman Filtering theory. Thistechnique u...

background: we aimed to extract the histogram features for text analysis and, to classify the types of bio medical waste (bmw) for garbage disposal and management. methods: the given bmw was preprocessed by using the median filtering technique that efficiently reduced the noise in the image. after that, the histogram features of the filtered image were extracted with the help of proposed modifi...