Matching the similarity between two units of data occurs as a frequent task in video or image analysis. The parameters of matching techniques are level of abstraction of features, distance measures and normalization o...
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ISBN:
(纸本)0819439886
Matching the similarity between two units of data occurs as a frequent task in video or image analysis. The parameters of matching techniques are level of abstraction of features, distance measures and normalization of features, if supported, or else the method of relatively weighing the features. Most multimedia analysis systems employ only low level features with distance measures similar to Euclidean distance, with no method to automatically generate the weights of the features and thus are ineffective in replenishing suitable matches to the user's demands. We argue for shifting the burden of mapping the feature space with relevant categories from the user to the multimedia analysis system. In this paper, a Bayesian Framework is presented where the evaluation of the parameters of classification and especially the relevancy of each feature with respect to each class is performed automatically. The probabilistic framework is extended to work well for generalized multi-modal distribution of a particular class over the feature space. Theoretical foundation is developed to provide simultaneously existing multiple views to an image or a video sequence. The low-level features can be synthesized with intelligent association to furnish high-level features, which could be more meaningful to the user. The significance of this work is presented by comparing with a system which employs a unsophisticated approach similar to common systems where feature vector of query image and feature vector of template image are compared by means of weighted Euclidean distance. The superiority of our approach is presented over the database consisting of 300 video sequences comprising of diverse video classes.
This paper proposes a novel rotational method on AC coefficient pairs to embed data into a JPEG compressed image. The purpose is to improve the carrier capacity of [1] while maintaing its original feature in controlli...
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ISBN:
(纸本)9781479902880
This paper proposes a novel rotational method on AC coefficient pairs to embed data into a JPEG compressed image. The purpose is to improve the carrier capacity of [1] while maintaing its original feature in controlling quality degradation. The proposed method exploits two properties in the quantized AC coefficients, namely, large magnitude and short run of zeros for low frequency subbands, and vice versa. The coefficients are first grouped into pairs and then rotated to the left or right directions to create distinctive states, where each can be utilized to represent external data. The AC coefficients are not modified and no additional AC coefficients are introduced for data embedding. However, preprocessing is needed so that all blocks satisfy the properties assumed to ensure correct data extraction and image recovery. The proposed method is rewritable because the host image can be re-utilized without causing further distortion. Experiments were conducted to verify the basic performance of the proposed method. On average, the proposed method is able to embed up to similar to 9318 bits in the test images of quality factor 80.
In this work we discuss several approaches fur designing fractal quantizers in the context of hybrid wavelet-fractal image compression algorithms. Moreover different subband-structures are compared concerning their su...
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ISBN:
(纸本)0819427497
In this work we discuss several approaches fur designing fractal quantizers in the context of hybrid wavelet-fractal image compression algorithms. Moreover different subband-structures are compared concerning their suitability for subsequent fractal quantization.
Most existing 3D image quality metrics use 2D image quality assessment (IQA) models to predict the 3D subjective quality. But in a free viewpoint television (FTV) system, the depth map errors often produce object shif...
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ISBN:
(纸本)9781479902880
Most existing 3D image quality metrics use 2D image quality assessment (IQA) models to predict the 3D subjective quality. But in a free viewpoint television (FTV) system, the depth map errors often produce object shifting or ghost artifacts on the synthesized pictures due to the use of Depth image Based Rendering (DIBR) technique. These artifacts are very different from the ordinary 2D distortions such as blur, Gaussian noise, and compression errors. We thus propose a new 3D quality metric to evaluate the quality of stereo images that may contain artifacts introduced by the rendering process due to depth map errors. We first eliminate the consistent pixel shifts inside an object before the usual 2D metric is applied. The experimental results show that the proposed method enhances the correlation of the objective quality score to the 3D subjective scores.
In this paper, we present a novel image scaling method that employs a mesh model that explicitly represents discontinuities in the image. Our method effectively addresses the problem of preserving the sharpness of edg...
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ISBN:
(纸本)9781538607008
In this paper, we present a novel image scaling method that employs a mesh model that explicitly represents discontinuities in the image. Our method effectively addresses the problem of preserving the sharpness of edges, which has always been a challenge, during image enlargement. We use a constrained Delaunay triangulation to generate the model and an approximating function that is continuous everywhere except across the image edges (i.e., discontinuities). The model is then rasterized using a subdivision-based technique. visual comparisons and quantitative measures show that our method can greatly reduce the blurring artifacts that can arise during image enlargement and produce images that look more pleasant to human observers, compared to the well-known bilinear and bicubic methods.
Impulse noise is commonly encountered during image transmission and many methods have been proposed to remove it. Although it is now possible to recover the true image reasonably well, even under severe noise (90% pix...
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ISBN:
(纸本)9781479961399
Impulse noise is commonly encountered during image transmission and many methods have been proposed to remove it. Although it is now possible to recover the true image reasonably well, even under severe noise (90% pixel contamination), essentially all methods published so far follow the standard procedure of noisy pixel detection/classification and then noisy pixel value reconstruction, without any further processing. In this paper we show an interesting empirical discovery that the traditionally denoised image tends to have the estimation error with a Laplacian distribution, which makes it possible to add a postprocessing stage to denoise the traditionally obtained result with this new type of noise. We propose a practical algorithm within this new framework and experimental results show that superior results can be obtained over previously published methods.
imageprocessing and analyzing images of the operation is to always ask about their quality, whether the quality is increased or decreased? image Quality Assessment techniques is required for prediction of quality of ...
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ISBN:
(纸本)9781479933587
imageprocessing and analyzing images of the operation is to always ask about their quality, whether the quality is increased or decreased? image Quality Assessment techniques is required for prediction of quality of the image. Human visual System (HVS) has been widely incorporated in estimating the quality of the image, as human is the ultimate observer of the image. In this work, Author investigated the SSIM index depends upon correlation based filtering like Gaussian low pass filter, averaging filter, Circular averaging filter and motion filter, also mean square error and peak signal to noise ratio is used.
In this work we apply techniques originating from classical fractal still-image coding to block-matching motion compensation algorithms for digital video compression. Especially the method of adapting the gray-values ...
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ISBN:
(纸本)0819427497
In this work we apply techniques originating from classical fractal still-image coding to block-matching motion compensation algorithms for digital video compression. Especially the method of adapting the gray-values in image blocks of the current frame to those in blocks of the reference-frame shows promising performance.
This paper presents an energy efficient VLSI architecture for motion estimation using imageprocessing assisted voltage overscaling (VOS). Motion estimation is the most computationally expensive block inside any video...
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ISBN:
(纸本)9780819469946
This paper presents an energy efficient VLSI architecture for motion estimation using imageprocessing assisted voltage overscaling (VOS). Motion estimation is the most computationally expensive block inside any video encoder, typically consuming 40-60% of the total power. This work focuses on using VOS to reduce power consumption at the expense of marginal loss of visual quality. Some imageprocessing techniques are used to assist VOS so that a better trade-off between power and visual quality can be achieved. The design is demonstrated using full search and three step search algorithms. Simulation results in 65mn CMOS technology show that the proposed technique can save up to 30% power at the cost of 0.5dB loss of PSNR.
We proposed in this paper a retina model based approach for image quality assessment. The retinal model is consisted of an optical modulation transfer module and an adaptive low-pass filtering module. We treat the mod...
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ISBN:
(纸本)9781479902880
We proposed in this paper a retina model based approach for image quality assessment. The retinal model is consisted of an optical modulation transfer module and an adaptive low-pass filtering module. We treat the model as a black box and design the adaptive filer using an information theoretical approach. Since the information rate of visual signals is far beyond the processing power of the human visual system, there must be an effective data reduction stage in human visual brain. Therefore, the underlying assumption for the retina model is that the retina reduces the data amount of the visual scene while retaining as much useful information as possible. For full reference image quality assessment, the original and distorted images pass through the retinal filter before some kind of distance is calculated between the images. Retina filtering can serve as a general preprocessing stage for most existing image quality metrics. We show in this paper that retina model based MSE/PSNR, though being straightforward, has already state of the art performance on several image quality databases.
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