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We consider the motion-compensated temporal prediction loop at the heart of modern video coders. Rather than using motion-compensated reference frame blocks directly as predictors, we incorporate their spatially-filtered versions into the prediction loop. We design adaptive filters that are geared toward successful prediction over sophisticated temporal evolutions involving lighting changes, focus...
Generalized convolution and correlation theorems for the Wigner-Ville distribution (transform) associated with linear canonical transform (WVD-LCT) are established. The proposed theorems are modified forms of the convolution and correlation theorems of the linear canonical transform and classical Wigner-Ville distribution.
This paper introduces an efficient approach towards blind deblurring of palm print images suffered from severe motion blur. First an improved Hough transform method is proposed to detect the blur angle and length of palm print image accurately. Analysis of blurred image is performed in Fourier domain which contains important information about the blur orientation of an image. After detecting the blur...
We introduce a general-dimensional, kernel-independent, algebraic fast multipole method and apply it to kernel regression. The motivation for this work is the approximation of kernel matrices, which appear in mathematical physics, approximation theory, non-parametric statistics, and machine learning. Existing fast multipole methods are asymptotically optimal, but the underlying constants scale quite...
We describe a new computational approach to edge detection. Our digital algorithm emulates propagation of light through a physical medium with specific nonlinear diffractive property. The method uses the phase profile of the output complex-amplitude image to identify the edges with different strength in a digital image. This technique is related to the recently introduced Discrete Anamorphic Stretch...
This paper presents an effective single image spatially variant motion blur removal technique. Motion blur during the image capture occurs due to the relative motion between the capturing device and image being captured. This blur becomes spatially variant if it varies with position in an image. Removal of such space/shift variant blur from a single image is a challenging problem. To solve this problem,...
In this paper, we present a rich image representation which is robust to illumination, facial expression and scale variations. For this aim, firstly, we propose a novel dense local image representation method based on Walsh Hadamard Transform (WHT) called Local WHT (LWHT). LWHT is the application of WHT to each pixel of an image to decompose it into multiple components, called LWHT maps. Secondly,...
Information extraction from signals has been a long time research topic and numerous signal transforms have been defined for the same purpose. In this paper, a comparative study of various signal transforms on basis of time-frequency (TF) resolution, cross-terms suppression and maximum information content has been presented. The transforms considered for the analysis are Frequency domain transforms,...
HEVC (High Efficiency Video Coding) is the newest video compression standard. Compared with the previous standards, the Coding efficiency is greatly improved at the cost of much higher codec complexity. So, many people improve the HEVC algorithm from the hardware level and software level. For the IQ/IT (inverse quantization/inverse transform) part, HEVC just processes one TU block one by one. And...
At electronic system level (ESL), the existing design flow lacks of an effective design methodology to transform transaction level modeling (TLM) communications to the real bus protocol (e.g., the AXI bus protocol). Therefore, after the design is verified through TLM 2.0 simulation, the designers need to spend a lot of human efforts (by themselves) to transform TLM 2.0 communication mechanisms to...
The main task of computer-aided diagnosis (CADx) is to differentiate the pathological stages to which each detected colorectal lesion belongs, especially to differentiate hyperplastic polyps, which are non-neoplastic and seldom show malignant potential, from neoplastic lesions, which are malignant or at risk for malignant transformation. If we could extract useful pattern information from detected...
In this paper, we try to hybrid projection twin support vector machine (PTSVM) and Extreme Learning Machine(ELM). The experiments shows that ELM generally out performs SVM/LS-SVM in various kinds of cases. PTELM tries to use ELM to overcome the shortness of PTSVM, which lacks of flexibility to change nonlinear kernel mapping for complex samples distribution regions. In order to overcome the shortness...
Motion blur is a most common degradation present in the photograph captured from hand held camera. Minute visual details are lost and spreaded over pixels creating smearing impact in captured image due to motion blur. It's hazardous for machine vision application and should be corrected by any restoration methodology. As no information is available about kind of degradation and true image, restoration...
In field of autonomous and intelligent vehicles, the goal of pedestrian classification is to reduce amount of accidents. The object classification accuracy depends on the type of classifier and the extracted object features used for classification. Support Vector Machines (SVM), is considered the most effective classifier for this task. However, it depends on a number of factors that require researchers...
High-performance computing (HPC) applications have been specialized for their target systems to achieve high performances. Hence, their performances are not portable to other systems. This performance portability problem leads to higher costs for maintaining HPC applications, because the life of an HPC application is usually much longer than that of an HPC system. Therefore, an HPC application needs...
Researchers in various fields are using optical microscopy to acquire very large images, 10000 -- 200000 of pixels per side. Optical microscopes acquire these images as grids of overlapping partial images (thousands of pixels per side) that are then stitched together via software. Composing such large images is a compute and data intensive task even for modern machines. Researchers compound this difficulty...
This paper proposes a language-independent method for segmenting text lines from handwritten document images. Our method is based on the seam carving, which has been already used for text line segmentation, but in order to tolerate multi-skewed text lines even in the same document image, we propose a constrained seam carving method, which can constrain energy to be passed along the connected components...
Compressed sensing (CS) is a promising approach to accelerate dynamic magnetic resonance imaging (MRI). Most existing CS methods employ linear sparsifying transforms. The recent developments in non-linear or kernel-based sparse representations have been shown to outperform the linear transforms. In this paper, we present an iterative non-linear CS dynamic MRI reconstruction framework that uses the...
In this paper, we propose a sparse representation method for traffic sign recognition based on similar class. The method needs to presort traffic signs as four main class according to its similar feature. We named the four main class as speed-limiting class, warning class, directive class and no-rules class. Then the method can be divided into two phases. First, we use a combination of PCA (Principal...
The past twenty years has seen the explosion of the "shape zoo": myriad shape representations, each with pros and cons. Of the varied denizens, distance transforms and density function shape representations have proven to be the most utile. Distance transforms inherit the numerous geometric advantages of implicit curve representations while density functions are unmatched in their approach...
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