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Existing video coding standards always employ line-based intra prediction for intra frame coding. However, it sometimes does not perform well for the bottom-right boundary pixels due to the low correlation with the referenced pixels. In this paper, we propose a novel joint line and pixel prediction (JLPP) method to compensate the performance degradation of boundary pixels. In JLPP, each block is partitioned...
End-to-end distortion estimation is critical to effective error-resilient video coding. The recursive optimal per-pixel estimate (ROPE) is a known approach to compute up to second moments of decoder-reconstructed pixels, and thereby optimally estimate the distortion. ROPE accurately accounts for encoding/decoding operations that are recursive in the pixel domain, and their interaction with packet...
India is praised for its rich past and the culture. The rich heritage of the country has been carried over generations through the manuscripts and historic writings. A great deal of effort is being made to prevent their further degradation. A lot of research is also done in finding methods to digitize these documents so that they can be immortalized. But in order to achieve this, the noise in the...
We present a novel method to automatically extract panels from figures in biomedical articles. Our method consists of figure (or panel) classification and panel segmentation. Figure classification determines the existence of photograph in a figure. A Gaussian model is constructed for photographs and plots. Figures and panels are evaluated based on the model to determine their class. If it contains...
A new model of decomposing an image hierarchically into direction-adaptive subbands using pixel-wise direction estimation is presented. For each decomposing operation, an input image is divided into two parts: a base image subsampled from the input image and subband components. The subband components consist of residuals of estimating the pixels skipped through the subsampling, which ensures the invertibility...
In this paper we analyze the neural progenitor cells in a time-lapse sequence to find position, shape, motility and ancestor of each cell in the frame. Because of the complex nature of cells, the ability to distinguish a cell from the background of an image for automatic quantification remains a challenging task. By using morphological techniques we are able to make a better selection of blob-like...
Nighttime imagery poses significant challenges to its enhancement due to loss of color information and limitation of single sensor to capture complete visual information at night. To cope with this challenge, multiple sensors are used to capture reliable nighttime imagery which presents additional demands for reliable visual information fusion. In this paper, we present a system, Scarf, which proposes...
The computation of stereoscopic depth is an important field of computer vision. Although a large variety of algorithms has been developed, the traditional correlation-based versions of these algorithms are prevalent. This is mainly due to easy implementation and handling but also to the linear computational complexity, as compared to more elaborated algorithms based on diffusion processes, graph-cut...
In this paper, to enable a fast and robust system for automatically recognizing license plates with various appearances, new and simple but efficient algorithms are developed to segment characters from extracted license plate images. Our goal is to segment characters properly from a license plate image region. Different from existing methods for segmenting degraded machine-printed characters, our...
Ghosts are digital images that contain highly constrained patterns of signed pixel values. The pixels are located so as to create zero-sums when discrete projections are taken across the image at a pre-determined set of angles. Ghosts can be applied to create image/anti-image pairs. An image that is entangled with its anti-image can be used to achieve forward error-correction in redundant data transmission...
Robust image hashing seeks to transform a given input image into a shorter hashed version using a key-dependent non-invertible transform. These image hashes can be used for watermarking, image integrity authentication or image indexing for fast retrieval. This paper introduces a new method of generating image hashes based on extracting Higher Order Spectral features from the Radon projection of an...
Symmetric-SIFT is a recently proposed local technique used for registering multimodal images. It is based on a well-known general image registration technique named Scale Invariant Feature Transform (SIFT). Symmetric SIFT makes use of the gradient magnitude information at the image's key regions to build the descriptors. In this paper, we highlight an issue with how the magnitude information is used...
We present a method for matching image local features, specifically SIFT features, to a database of learned object features for the purpose of object recognition and localisation. Our approach differs from existing methods by taking into account the geometric consistency of matched features concurrently with their description vector similarity. As a result we do not need to over-constrain the description...
Biometric hash finds extensive applications in multimedia security systems. Biometric hashing schemes combine biometric features with random numbers for robust and secure human authentication or recognition. A novel biometric hashing scheme which is secure and robust to lighting changes is proposed in this paper. First, the local binary pattern (LBP) based histogram sequence or vector is employed...
In this paper, we present an algorithm to remove high-frequent texture and detail from images without destroying high-level image structure or introducing artificial edges. While based on the same general framework, this “image simplification” filter differs from noise filtering methods such as bilateral filtering by its frequency-selectivity and edge awareness. Applications include artistic filtering...
This work presents an efficient image fusion of the visible range (VR) and infrared range (IR) images for image enhancement in digital still camera. Fusion is achieved by estimating the weighting parameters which contain the properties of IR image and by combining the VR and IR images using the parameters. Specifically, the weighting parameters are calculated from the estimated illumination and detail...
In this paper, we present an efficient rectification algorithm for un-calibrated multi-view images based on SIFT (Scale-invariant feature transform) feature matching. Un-calibrated rectification is necessary for some specific occasions and we extend generic stereo pair rectification to multi-view camera array with projection shift method. We bring in SIFT algorithm to extract and match features (key...
The goal of multi-modal image fusion is to combine complementary information from multisensory data such that the fused image is more suitable for the purpose of human visual perception, computer-processing tasks and detection applications. In this paper, we first use independent component analysis (ICA) as the primary transformation to obtain adaptive analysis bases trained by similar reference images;...
In this paper, we propose a novel region grouping approach to shape matching. It is proposed as an alternative region based approach to the traditional edge based shape matching using distance transforms. It has the advantage of obtaining a higher detection rate and obtaining meaningful object segmentation simultaneously. Each image is first segmented into image regions, and possible matches are found...
In this paper, we propose an approach to preserve a crucial visual cue in color to grayscale transformation: attention. The main contributions are three folds: 1) preserving visual attention is more biological plausible than preserving other low level cues, which makes our method more reasonable in theory from both biological and psychological aspects, 2) We treat the saliency map from visual attention...
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