This paper presents two algorithms for detection of plain copy-move regions—fully matching fragments—in images. Both algorithms represent data of the fragment in the form of a hash value, where the hash function is ...
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The explosion of computational imaging has seen the frontier of imageprocessing move past linear problems, like denoising and deblurring, and towards non-linear problems such as phase retrieval. There has a been a co...
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ISBN:
(纸本)9781467399623
The explosion of computational imaging has seen the frontier of imageprocessing move past linear problems, like denoising and deblurring, and towards non-linear problems such as phase retrieval. There has a been a corresponding research thrust into non-linear image recovery algorithms, but in many ways this research is stuck where linear problem research was twenty years ago: Models, if used at all, are simple designs like sparsity or smoothness. In this paper we use denoisers to impose elaborate and accurate models in order to perform inference on generalized linear systems. More specifically, we use the state-of-the-art BM3D denoiser within the Generalized Approximate Message Passing (GAMP) framework to solve compressive phase retrieval in a variety of different contexts. Our method demonstrates recovery performance equivalent to existing techniques using fewer than half as many measurements. This dramatic improvement in compressive phase retrieval performance opens the door for a whole new class of imaging systems.
In this paper, we propose a novel scheme for image restoration (IR) employing a sequential decoding technique based on a tree search, known as Stack algorithm. The latter is a well-known method used for ID signal deco...
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ISBN:
(纸本)9781509018918
In this paper, we propose a novel scheme for image restoration (IR) employing a sequential decoding technique based on a tree search, known as Stack algorithm. The latter is a well-known method used for ID signal decoding in wireless communication systems. The main idea is to extend the Stack algorithm for image restoration (2D) and to exploit the information diversity conveyed by the channels (Multichannel) in order to restore the original image. To deal with the noisy case, a regularization term is introduced using the total variation and the wavelet transform. This method was tested on artificially degraded images (blurred and noisy). Obtained results confirm the relevance of the proposed approach.
Estimator algorithms rely on assumed laser stripe image profile to determine its peek with sub-pixel accuracy. They depend on light intensity readings around the peak and are susceptible to noise and saturation. Noise...
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ISBN:
(纸本)9781509018987
Estimator algorithms rely on assumed laser stripe image profile to determine its peek with sub-pixel accuracy. They depend on light intensity readings around the peak and are susceptible to noise and saturation. Noise and stripe intensity models are commonly used to synthesize and feed test data to estimator algorithms in order to evaluate their accuracy and robustness. For real-time 3D scanning applications estimator algorithms are expected to prefer less computationally demanding estimation techniques. Simple and accurate models of empirical noise and laser stripe profile could be used to improve testing and algorithms accuracy. Modular test setup for 3D scanning is utilized to project a laser stripe on the target with patterned surface. Laser stripe image is captured and processed to extract noise and surface pattern interference. Laser power modulation is used to generate series of captures with various stripe intensities. Captures are partitioned, analyzed and presented according to target surface properties and color channels. image noise interfering with sub-pixel peak detection is analyzed and noise model based on empirical data is proposed. Empirical laser stripe images are analyzed and novel simple laser stripe intensity profile model conforming to empirical data is proposed.
Accurate localization and fast tracking of interventional tools is an area of paramount importance in procedures with real-time MR guidance. Optically detunable radiofrequency (RF) coils are a robust method for the id...
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ISBN:
(纸本)9783319327037;9783319327013
Accurate localization and fast tracking of interventional tools is an area of paramount importance in procedures with real-time MR guidance. Optically detunable radiofrequency (RF) coils are a robust method for the identification of individual MR markers for MR-compatible robotics system. In this study, we describe a technique for localizing and tracking four RF coils. Each coil consists of a 3 mm diameter inductively coupled solenoid coil with a photoresistor that is optically tuned and detuned. In particular, by selecting only one marker to be MR visible per data collection repetition, this particular marker point of the manipulator is unambiguously distinguished. This technique allows simplification of both the data acquisition and the post processingalgorithms. A user-programmable microcontroller times the ON/OFF state of light sources and triggers the MR scanner so that a particular image collection depicts a specific RF coil or combination. Phantom studies at 1.5T demonstrated the technique illustrating the selective observation of one or multiple markers. The described technique can use imaging to track multiple points on an interventional device, such as the shaft of steerable catheters and the end-effectors of MR-compatible manipulators.
Increasing spatial resolution is often required in many applications such as entertainment systems or video surveillance. Apart from using higher resolution sensors, it is also possible to apply super-resolution algor...
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ISBN:
(纸本)9781467399623
Increasing spatial resolution is often required in many applications such as entertainment systems or video surveillance. Apart from using higher resolution sensors, it is also possible to apply super-resolution algorithms to realize an increased resolution. Those methods can be divided into approaches that rely on only a single low resolution image or on multiple low resolution video frames. While incorporating more frames into the super-resolution is beneficial for the resolution enhancement in principle, it is also likely to introduce more artifacts from inaccurate motion estimation. To alleviate this problem, various weightings have been proposed in the literature. In this paper, we propose an extended dual weighting scheme for an interpolation-based super-resolution method based on voronoi tessellation that relies on both a motion confidence weight and a distance weight. Compared to non-weighted super-resolution, the proposed method yields an average gain in luminance PSNR of up to 1.29 dB and 0.61 dB for upscaling factors of 2 and 4, respectively. visual comparisons substantiate the objective results.
Diabetic retinopathy (DR) is the most frequent complication of diabetes mellitus that affects vision to the point of causing blindness. In advanced stages its progress can be delayed with laser photocoagulation which ...
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ISBN:
(纸本)9781509018918
Diabetic retinopathy (DR) is the most frequent complication of diabetes mellitus that affects vision to the point of causing blindness. In advanced stages its progress can be delayed with laser photocoagulation which leaves behind marks on the retina. Modern screening programs rely on automatic diagnostic algorithms to detect signs of DR in patients. These systems performance may be impaired when patient retina presents marks from previous laser photocoagulation treatments. Since these patients are already being treated, it is desirable to detect and remove them from the screening program. An algorithm that automatically detects the presence of laser marks in retinal images using tree-based classifiers is proposed and the results on its performance are obtained and described. Two new public accessible datasets containing retinal images with laser marks are provided in this paper.
The possibility of using contour analysis was examined for solving the image superimposition problem in multispectral computer vision systems (images that are obtained from the sensors of this system and images that a...
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The article is devoted to solving the problem of onboard processing of hyperspectral data for subsequent transmission via the communication channels in systems of remote sensing. A compression method based on the hier...
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The article is devoted to solving the problem of onboard processing of hyperspectral data for subsequent transmission via the communication channels in systems of remote sensing. A compression method based on the hierarchical grid interpolation is used as the basic algorithm of data compression necessary to reduce the amount of transmitted information. In this article, the method is adapted for onboard data processing. The specificity of hyperspectral imaging is taken into account when developing an algorithm of stabilization of the rate of compressed data formation. Computational experiments show that the efficiency of the proposed algorithms is sufficient for the transmission of hyperspectral remote sensing data under the limited capacity of the buffer memory and the communication channel bandwidth.
In distributed sensing systems that use compressed videos for video analysis tasks, the lossy compression of videos can damage the accuracy of object detection, which is an essential step for various vision applicatio...
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ISBN:
(纸本)9781467399623
In distributed sensing systems that use compressed videos for video analysis tasks, the lossy compression of videos can damage the accuracy of object detection, which is an essential step for various vision applications. This paper aims at constructing a new quality model to predict the performance of object detection. To achieve this goal, a distorted video database is constructed by applying object detection algorithms on a variety of videos that are compressed with different levels of distortion. Based on the database, a parametric quality prediction model is built using features that can be easily obtained during the encoding process. Experimental results show that the model can achieve high accuracy in predicting the performance of object detection. The model introduces low computation cost and can be easily integrated in video encoders for rate-quality optimization.
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