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Non-Bayer color filter array (CFA) sensors have recently drawn attention due to their superior compression of spectral energy, ability to deliver improved signal-to-noise ratio, or ability to provide high dynamic range (HDR) imaging. Demosaicking methods that perform color interpolation of Bayer CFA data have been widely investigated. However, a bottleneck to the adaption of emerging non-Bayer CFA...
Haze removal, which is also referred to as image dehazing, has been extensively used to improve the visibility in images captured under inclement weather. In particular, the dark channel prior (DCP)-based single image dehazing has received the greatest amount of interest due to its superior performance. However, since the DCP is based on the characteristics of natural outdoor images, its reliability...
Determining the make and model of an image's source camera is an important forensic problem. While significant research has been conducted towards developing new camera model identification algorithms, little research has focused on controlling the computational cost of these algorithms. This becomes an important issue if forensic algorithms are to be used in “big data” scenarios. In this paper, we...
Cutting out and object and estimate its transparency mask is a key task in many applications. We take on the work on closed-form matting by Levin et al.[1], that is used at the core of many matting techniques, and propose an alternative formulation that offers more flexible controls over the matting priors. We also show that this new approach is efficient at upscaling transparency maps from coarse...
Depth estimation from single image is an important component of many vision systems, including robot navigation, motion capture and video surveillance. In this paper, we propose to apply a structure forest framework to infer depth information from single RGB image. The core idea of our approach is to exploit the structure properties exhibit in local patches of depth map to learn the depth level for...
In this work, we introduce a new fusion model whose objective is to fuse multiple region-based segmentation maps to get a final better segmentation result. This new fusion model is based on an energy function originated from the global consistency error (GCE), a perceptual measure which takes into account the inherent multiscale nature of an image segmentation by measuring the level of refinement...
The morphological similarity of anatomical structures is essential to the study of the species evolution. In this paper, we investigate the unsupervised shape similarity analysis by a random-forest-based metric. The dense continuous deformation fields are employed as the shape descriptors. The forest is built when given the unlabeled deformation fields, where the leaves can be seen as an optimal clustering...
We propose a method for the color stabilization of cinema shots coming from different cameras that use unknown logarithmic encoding curves. The log-encoding curves are approximated by a concatenation of gamma-curves, whose values are accurately computed using image matches. The color stabilization procedure, based on the generic color processing pipeline of a digital camera, can be performed after...
In this paper, we propose a novel method for light field imaging. Previous systems are difficult to obtain multi-viewpoint images (sub-images) at the high-resolution. In order to overcome this problem, we propose a two-layer light field imaging system by using an organic photoelectric conversion film (OPCF). Our imaging system places the OPCF having the green spectral sensitivity onto the micro-lens...
Human detection in RGB-D images is an important yet very challenging task in computer vision. In this paper, we propose a novel human detection approach in RGB-D images, which integrates ROI (region-of-interest) generation, depth-size relationship estimation and a human detector. Our approach has the following advantages: 1) ROI generation and depth-size relationship estimation take full advantage...
State-of-the-art single image dehazing algorithms have some challenges to deal with images captured under complex weather conditions because their assumptions usually do not hold in those situations. In this paper, we develop a deep transmission network for robust single image dehazing. This deep transmission network simultaneously copes with three color channels and local patch information to automatically...
Estimation of salient regions in an input video is an active area of research due to its wide applications. In this paper, we propose a novel algorithm to estimate the eye gaze movement in a video using motion, color and structural cues with minimum outliers. The algorithm is generalized to capture salient information for the videos taken under different camera motions. The entire algorithm is parallelizable...
We introduce an effective technique to enhance night-time hazy scenes. Our technique builds on multi-scale fusion approach that use several inputs derived from the original image. Inspired by the dark-channel [1] we estimate night-time haze computing the airlight component on image patch and not on the entire image. We do this since under night-time conditions, the lighting generally arises from multiple...
Detecting roads using monocular vision is a very challenging task as the detection algorithm must be able to deal with complex real-road scenes. In this paper, we describe an algorithm for general path segmentation. There are three main technical contributions of the approach. First, a path segmentation framework is presented, which formulates road detection as a Bayesian posteriori estimation problem...
We presented a systematic study of how subject head motion affects pulse rate estimation using photoplethysmography from the subject's face. We evaluated the performance at various steps in the process, including object tracking, skin blob detection, pulse signal extraction and pulse rate estimation. We demonstrated that the signal-to-noise ratio of the power spectrum is a good indicator of signal...
The intensity of the light observed from every position and direction in a real scene can be modeled as a highdimensional field, namely the plenoptic function. This field codes the radiance information as a function of space, orientation, wavelength, and time. In the scope of depth estimation, several strategies have been developed to obtain a representation of the spatial structure of a scene. However,...
Haze or fog jeopardizes both environment and image quality, which degrades the quality of subsequent computer vision algorithms. Recently haze removal method in image processing makes significant progress. The existing methods usually require complicated manual parameters setting according to the variance of input. Among them, dehazing method based on dark channel prior is considered to be the most...
In this paper, we present an efficient single image dehazing approach via scene-adaptive segmentation and improved dark channel model. First, we detect the image depth information and segment the raw image into the close view and distant view. Then, we utilize the minimum channel image of distant view to regularize the atmospheric veil and simultaneously estimate its light value of close view within...
Sugarcane is one of the most important economic crops in south China. It's of practical value to quickly assess the leaf area index (LAI) of sugarcane and evaluate its growing state. Field-based or in situ measurements are very labor intensive and time consuming, while satellite images are relatively coarse and unsuitable for real-time crop monitoring, not to mention the cloud-prone climate in south...
In this paper, we present a new framework for building change detection from monocular aerial imagery that automatically predicts building candidates based on adaptive local textural features with successive background removal. An adaptive local entropy feature is developed based on quadratic regression and Random Sample Consensus (RANSAC) for extracting potential building candidates. Then a majority...
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