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Single-image blind deblurring could be considered as an important preprocessing step in imaging information fusion. Its purpose is to simultaneously estimate blur kernel and latent sharp image from only one observed blurred image. Blind deblurring has been attracting increasing attention in the fields of image processing, computer vision, computational photography, etc. However, it is a typically...
Smart vision systems on a chip are promising for embedded applications. Currently, flexibility in the choice of integrated pre-processing tools is obtained at the expense of total silicon area and fill factor, which are otherwise optimized provided that the sensor performs a specific task. We propose a new architecture based on macropixel-level processing to improve the trade-off by using the same...
Video super-resolution (SR) is an inverse problem, which has gained much attention in these years. One of the core issues is how to better suppress noise and better preserve the edge. Multi-non-local regularization (MNLR) algorithm is efficient to reduce noise by utilizing the useful information from the correlated frames, but it might also cause some loss of high frequency at the same time. Multi-scale...
Approximate computing improves digital circuit performance by relaxing the requirement of performing exact calculations. In this paper, we investigate the use of approximate adders in the final stage of a carry save multiplier-accumulator (MAC), designed for image filtering application. We propose a design flow based on synthesis tools, starting from HDL description. After a first step in which an...
Image edge information is very important in application areas such as machine learning, image processing, stereo vision, object tracking and pattern recognition. Intensity discontinuities or sudden intensity changes in a region are indicative of the edge region in that region. Although there are many approaches to detecting edge, generally intensity discontinuities or sudden intensity changes in a...
Saliency detection is a fundamental problem in computational and cognitive sciences. Nowadays, graph-based methods are widely applied to saliency detection including manifold ranking(MR) method, which is shown to be fast and effective. However, because of only using a single feature and imperfect selection strategy for background seeds, MR has a poor performance in some circumstances. In order to...
Staircases are among the most common architectural features in urban environments. In this paper, we describe a method for detecting indoor staircases from depth images. The objective of this development is to aid visually impaired people in perceiving the environment, especially in unfamiliar places. This method is based on the detection and clustering of patches that have the surface normal vectors...
In this paper, a novel fast support vector machine (SVM) method combining with the deep quasi-linear kernel (DQLK) learning is proposed for large scale image classification. This method can train large-scale dataset with SVM fast using less memory space and less training time. Since SVM classifiers are constructed by support vectors (SVs) that lie close to the separation boundary, removing the other...
The given work describes a new technique of image segmentation, in particular for building detection on radar or infrared Earth-observation images. The method is based on property of most man-made objects which consist in straight edges and mostly right angles. The developed 2D adaptive image filter assists to detect straight edges even if given image fragment has a low contrast and has been extremely...
In this paper, hardware implementation of edge detection at real time video signals using Sobel, Robert, Prewitt and Laplacian filters based on FPGA is explained. Besides, filters are compared in many ways. Edge detection is an elemantary and fundamental tool for image segmentation and feature extraction. Very high speed hardware like FPGA's are used to implement the image and video processing algorithms...
Handwriting recognition has been a major topic of research since past many years. There have been several approaches to handwriting recognition but the recognition of handwritten characters using deep learning has been a hot topic of research in the past five years. This paper proposes a method of converting handwritten text into speech at real time using the concept of deep neural networks. Moreover...
Edge bundling techniques provide a visual simplification of cluttered graph drawings or trail sets. While many bundling techniques exist, only few recent ones can handle large datasets and also allow selective bundling based on edge attributes. We present a new technique that improves on both above points, in terms of increasing both the scalability and computational speed of bundling, while keeping...
As modern FPGAs evolve to include more heterogeneous processing elements, such as ARM cores, it makes sense to consider these devices as processors first and FPGA accelerators second. As such, the conventional FPGA development environment must also adapt to support more software-like programming functionality. While high-level synthesis tools can help reduce FPGA development time, there still remains...
This paper proposes the method of vehicle license plate recognition, which is essential in the field of intelligent transportation system. The purpose of the study is to present a simple and effective vehicle license plate detection and recognition using non-bling image de-blurring algorithm. The sharpness of the edges in an image is restored by the prior information on images. The blue kernel is...
This paper presents the implementation of image edge detection on Heterogeneous System Architecture (HSA). HSA which includes ARM processor, Coprocessor and FPGA are compared with x64 CPU in terms of performance and power consumption. The experimental results show that although the best execution time is from x64 CPU, HSA has 50 times more energy efficiency. Also, HSA can exploit coprocessors and...
In this work we address the problem of blind deblurring using a single space-variantly defocused image containing text. We estimate both the all-in-focus image and the blur map corresponding to the space-variant point spread function of the finite aperture camera. Since this problem is highly ill-posed we exploit a recently proposed technique [1] to obtain an initial estimate of the space-variant...
Interpolation tool plays a vital role in estimating missing values. This classical problem aims to preserve the structural information-edges and textures, in the resultant image. In this process of developing a continuous function, distractions such as blur, noise or other artifacts should not be entertained. This paper provides an overview of commonly used interpolation algorithms. Comparative discussions...
Breast cancer is the foremost cause of morbidity and mortality among womenfolk. India has 17% of world's population suffering from breast cancer. World Health Organization's International agency for Research on Cancer (IARC) estimates that more than 4,00,000 women die every year due to breast cancer. Thus early identification of breast cancer plays a vital role in reducing the mortality rate. Medical...
In this paper, we propose a blind motion deblurring method based on sparse representation and structural self-similarity from a single image. The priors for sparse representation and structural self-similarity are explicitly added into the recovery of the latent image by means of sparse and multi-scale nonlocal regularizations, and the down-sampled version of the observed blurry image is used as training...
This paper presents an image upsampling method. Joint-bilateral filtering has been successfully applied to this problem that upsample “target” images using high-resolutional “control” images. In this filtering, the kernel is a product of weights representing spatial proximity and color (or intensity) proximity of the “control” image. However, when the “target” image involves textures that are invisible...
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