this paper proposes a novel framework that unifies the concept of sparsity of a signal over a properly chosen basis set and the theory of signal reconstruction via compressed sensing in order to obtain a high-resoluti...
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ISBN:
(纸本)9781479915880
this paper proposes a novel framework that unifies the concept of sparsity of a signal over a properly chosen basis set and the theory of signal reconstruction via compressed sensing in order to obtain a high-resolution image derived by using a single down-sampled version of the same image. First, we enforce sparse overcomplete representations on the low-resolution patches of the input image. then, using the sparse coefficients as obtained above, we reconstruct a high-resolution output image. A blurring matrix is introduced in order to enhance the incoherency between the sparsifying dictionary and the sensing matrices which also resulted in better preservation of image edges and other textures. When compared withthe similar techniques, the proposed method yields much better result both visually and quantitatively.
An image captured in dark environment usually has ambient illumination, but the image looks dark and noisy. However, the use of flash can introduce unwanted artifacts such as sharp shadows at silhouettes, red eyes, an...
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ISBN:
(纸本)9781467385640
An image captured in dark environment usually has ambient illumination, but the image looks dark and noisy. However, the use of flash can introduce unwanted artifacts such as sharp shadows at silhouettes, red eyes, and non-uniform brightness in the image. We propose a new framework to enhance photographs captured in dark environments by combining the best features from a flash and a no-flash image. We use sparse and redundant dictionary learning based approach to denoise the no-flash image. A weighted least squares framework is used to transfer sharp details from the flash image into the no-flash image. We show that our approach is simple and able to generate better images than that of the state-of-the-art flash/no-flash fusion method.
this paper presents the design of STAR (Spatio-Temporal Analysis and Retrieval), an unsupervised Content Based Video Retrieval (CBVR) System. STAR's key insight and primary contribution is that it models video con...
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ISBN:
(纸本)9781479915880
this paper presents the design of STAR (Spatio-Temporal Analysis and Retrieval), an unsupervised Content Based Video Retrieval (CBVR) System. STAR's key insight and primary contribution is that it models video content using a joint spatio-temporal feature representation and retrieves videos from the database which have similar moving object and trajectories of motion. Foreground moving blobs from a moving camera video shot are extracted, along with a trajectory for camera motion compensation, to form the space-time volume (STV). the STV is processed to obtain the EMST-CSS representation, which can discriminate across different categories of videos. Performance of STAR has been evaluated qualitatively and quantitatively using precision-recall metric on benchmark video datasets having unconstrained video shots, to exhibit efficiency of STAR.
A Rough Set theory based closed form object boundary detection method has been suggested in this paper. Most of the edge detection methods fail in getting closed boundary of objects of any shape present in the image. ...
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ISBN:
(纸本)9781479915880
A Rough Set theory based closed form object boundary detection method has been suggested in this paper. Most of the edge detection methods fail in getting closed boundary of objects of any shape present in the image. Active contour based methods are available to get such object boundaries. the Multiphase Chan-Vese Active Contour Method is one of the most popular of such techniques. However, it is constrained with number of objects present in the image. the granular processing using Rough Set method overcomes this constraint and provides a closed curve around the boundary of the objects. this information can further be utilized in selection of similar patches for various imageprocessing problems such as image Denoising, image Super-resolution, image Segmentation etc. the proposed boundary detection method has been tested in presence of noise also. the experimental results have shown on synthetic image as well as on MRI of human brain. the performance of proposed method is found to be encouraging.
this paper discusses image decomposition problem of the 3-layer MRC model based coding of scanned (noisy) document images. A widely-used approach for document decomposition is to divide the document image into blocks ...
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ISBN:
(纸本)9781424442195
this paper discusses image decomposition problem of the 3-layer MRC model based coding of scanned (noisy) document images. A widely-used approach for document decomposition is to divide the document image into blocks and split the pixel histogram of each block into two halves by minimizing the sum of variance of its pixels withthe mean of the halms. We propose to split a block by minimizing the variance of one half with its minimum pixel and the variance of the other half with its maximum pixel. Our goal is to increase the gap between the two halves by avoiding splitting of any cluster of pixels into both halves. It should help reduce complexity of the generated mask. Moreover, we do not decompose a block if it has no edge points, again to reduce the mask complexity. We also implement a noise reduction heuristic in the mask layer to correct placement of transition pixels. We provide simple analysis and evaluate block energy in terms of the DCT coefficients of the resulting FG/BG layer blocks. Experimental results show that code size of the mask layer of our test images, obtained using proposed processing is reduced to nearly half of the mask obtained by a straightforward 3-MRC implementation.
In this paper, we propose a modified version of the standard proportional-derivative (PD) controller for biped locomotion. Our improvements stabilize the biped for high gain PD controllers. the main idea of our approa...
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ISBN:
(纸本)9781479915880
In this paper, we propose a modified version of the standard proportional-derivative (PD) controller for biped locomotion. Our improvements stabilize the biped for high gain PD controllers. the main idea of our approach involves applying corrective component to the existing framework, so that it prevents overshooting at high gains to stabilize the biped. We use pose control graphs to represent various gaits for the biped. We demonstrate with our improvements that the biped controller is stable while walking on irregular terrains. We also demonstrate that our formulation provides additional stability to the biped under minor impediments while in motion.
the spread of global smartphone market in the past decade has resulted in exponential growth of unstructured data, particularly in the form of multimedia, in the domain of social networking. Consequently, it has made ...
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ISBN:
(纸本)9781467385640
the spread of global smartphone market in the past decade has resulted in exponential growth of unstructured data, particularly in the form of multimedia, in the domain of social networking. Consequently, it has made data retrieval cumbersome, specially for the users. this has also posed as a major challenge in the development of new algorithms and technologies. this paper presents a context based search technique for personalized image retrieval, based on Logical Item-set Mining on image Hash-Tags given by the users. the tests were performed on Instagram image datasets of two different users, collected through a crawler and show promising results.
this paper proposes a transform domain data-hiding scheme for quality access control of images. the original image is decomposed into tiles by applying n-level lifting-based Discrete Wavelet Transformation (DWT). A bi...
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ISBN:
(纸本)9781424442195
this paper proposes a transform domain data-hiding scheme for quality access control of images. the original image is decomposed into tiles by applying n-level lifting-based Discrete Wavelet Transformation (DWT). A binary watermark image (external information) is spatially dispersed using the sequence of number generated by a secret key. the encoded watermark bits are then embedded into all DWT-coefficients of n(th)-level and only in the high-high (HH) coefficients of the subsequent levels using dither modulation (DM) but without complete self-noise suppression. It is well known that due to insertion of external information, there will be degradation in visual quality of the host image (cover). the degree of deterioration depends on the amount of external data insertion as well as step size used for DM. If this insertion process is reverted, better quality of images can be accessed. To achieve that goal, watermark bits are detected using minimum distance decoder and the remaining self-noise due to information embedding is suppressed to provide better quality of image. the simulation results have shown the validity of this claim.
We propose an evolving scheme to detect slow as well as fast moving objects in a video sequence. the proposed scheme employ, both spatio-temporal and temporal segmentation to obtain the Video Object plane and hence de...
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ISBN:
(纸本)9781424442195
We propose an evolving scheme to detect slow as well as fast moving objects in a video sequence. the proposed scheme employ, both spatio-temporal and temporal segmentation to obtain the Video Object plane and hence detection. We propose a Compound Markov Random Field Model as the a priori image model that takes into account the spatial distribution of the current frame, temporal frames and the edge maps of the temporal frames. the spatio-temporal segmentation is cast as a pixel labeling problem and the labels are the MAP estimates. the MAP estimates of a frame are obtained by a hybrid algorithm. the spatial segmentation of a given frame evolves to generate the spatial segmentation of the subsequent frames. the evolved spatial segmentation together withthe temporal segmentation produces the Video Object Plane (VOP) and hence detection. Our scheme does require the computation of spatio-temporal segmentation of the initial frame thus speeding up the whole process. the results of the proposed scheme are compared with JSEG method are found to be better in terms of the misclassification error
images taken in bad weather conditions like haze and fog suffer from loss of contrast and color shift. the object radiance is attenuated in the atmosphere and the atmospheric light is added to the scene radiance creat...
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ISBN:
(纸本)9781467385640
images taken in bad weather conditions like haze and fog suffer from loss of contrast and color shift. the object radiance is attenuated in the atmosphere and the atmospheric light is added to the scene radiance creating a veil like semi-transparent layer called airlight. the methods proposed till now assumes that the atmospheric light is constant throughout the image domain, which may not be true always. Here we propose a method that works under the relaxed assumption that the color of atmospheric light is constant but its intensity may vary in the image. We use the color line model to estimate the contribution of airlight in each patch and interpolate at places where the estimate is not reliable. We apply reverse operation to recover the haze free image.
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