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Automated classification algorithms have been applied to breast cancer diagnosis in order to improve the diagnostic accuracy and turnover time. However, classification accuracy, sensitivity and specificity could still be improved further. Moreover, reducing computational cost is another challenge as the number of images to be analyzed is typically large. In this paper, a novel Pixel N-gram approach...
This paper presents a new architecture and circuit design for colour x-ray pixel array detector read-out electronics, based on two circuit designs; the Bayer method of pixel arrangement and the full energy and special resolution circuit design, a simulation of the sub sampling architecture was made in MATLAB Simulink and the results shows that the propose architecture produces images with an image...
Image Histogram is useful in wide range of applications, it shows the image intensity distribution which is used in many image processing techniques. The processing time is very critical in real time applications, so the optimized and robust techniques are preferred. This paper is discussing a simple method for calculating histogram of the image with sampled Histogram which is similar to the histogram...
We describe a method of interpolation for a pixellated γ-radiation detector made of cadmium zinc telluride (CZT) with the goal to optimize its intrinsic spatial resolution. A similar method is known from silicon strip sensors where the interpolation improves the intrinsic spatial resolution over the single-strip digital resolution.
A new stereo vision system is presented, which is based on a low-power CMOS binary vision sensor, with embedded spatial contrast extraction and output data compression, through positional data coding. A novel disparity algorithm adapted to the output of the sensors has been developed. The algorithm has been simulated and tested on a real application. The presented system is targeted towards event-based...
Image super-resolution is the process by which additional information is incorporated to enhance a low resolution image thereby producing a high resolution image. In the simplest case super-resolution of a single image is a process of obtaining high-resolution image with more number of pixels with more resolving power. Therefore the super-resolved image should demonstrate an improvement in the perceived...
Image resolution enhancement is a usable process for many image processing applications such as geoscience studies, astronomy and geographical information systems. One of the traditional methods used to increase the image resolution is image interpolation but the potential problem associated with it is to magnify the image many times without loss in image clarity. However, all the classical linear...
A new segmentation method is proposed for high resolution remote sensing image. In the high-resolution remote sensing image, there is mass of data to be processed, and land objects exhibits strongly hierarchical and multiscale characters. In order to overcome the disadvantages of pixel-based hierarchical MRF model directly used on high-resolution remote sensed images, a hierarchically multiscale object-oriented...
Image resizing is widely applied in many fields such as medical image processing, consumer electronics and space application. In this paper, a two-phase adaptive image zooming method for gray-scale image magnifying is presented. For each local area under processing, the first work is trying to find a best-matched remote window within the image based on the structural similarity. The second step is...
This paper presents an extension of image rectification methods for an arbitrary number of views with aligned camera center. This technique can be used for stereoscopic rendering to enhance the perception comfort or for depth from stereo. In this paper, we first expose that epipolar geometry is not suited to solve this problem. Then we propose a non linear method that includes all the images in the...
Road detection from satellite images can be considered as a classification process in which pixels are divided into road and background classes and can be used as a criterion in road extraction process to discriminate between road and non road pixels. Apart from the spectral information, textural parameters and contextual information are usually used by human being in object recognition from images...
We present a multi-view 3D video acquisition and its processing system for multi-view 3D television (3DTV). The proposed hybrid camera system consists of three-color cameras and one time of flight (TOF) camera. Since currently available TOF cameras do not provide color images associated with the depth image, we use a beam splitter between the color camera of the center view and the TOF camera to minimize...
We present the principal aspects and the concept of a monocular combination of a scanning 3D time-of-flight sensor with a large-scale conventional 2D image sensor. While the 2D sensor profits from the whole field of view of an F-Mount photo film format lens, the smaller-sized 3D sensor is mounted onto a highly precise XY linear move stage. Thus, by the means of macro-scanning, the 3D sensor can be...
Multiview 3D videos can efficiently be represented using a mixed resolution multiview 3D video format that has a number of color and depth information with different resolutions. However, such a mixed resolution multiview video format would have a shortcoming on synthesizing virtual views between a low and a high resolution view. This paper provides an approach to synthesize virtual image from multi-view...
In 3DTV and free viewpoint imaging systems based on a view-plus-depth representation, depth compression is important for high-quality view synthesis. Several publications have proposed depth down-/up-sampling as part of the depth coding strategy. Recently, we proposed a depth up-sampling method which uses the high resolution view in the process of depth up-sampling. Actually, in 2007 Kopf et.al. already...
In this paper, a highly efficient pixel compensator architecture for the H.264/AVC standard is proposed which can provide both inter and intra prediction functions for luma and chroma components of pixels. By decomposing the algorithms used for both prediction methods into small micro-operation steps, a suitable common arithmetic unit architecture capable for performing these operations has been determined...
This paper presents a new image interpolation technique for enhancement of spatial resolution of images. The proposed algorithm uses the switching of existing Soft-decision Adaptive Interpolation (SAI) algorithm and Single Pass Interpolation Algorithm (SPIA) methods. We learn the error pattern in the interpolation process of SAI method and SPIA Method after interpolating downsampled version of LR...
Nowadays, digital pictures are usually captured at very high resolution ranged up to 12 mega-pixels. Limited by low-resolution display, we have to shrink the image. Signal processing theory tells us that optimal decimation requires low-pass filtering with a suitable cut-off frequency followed by down-sampling. In doing so, we need to remove lots of details. Subpixel-based down-sampling, taking advantage...
The real noise model corrupting the observed images is unknown and usually random statistical model. Consequently, classical SRR (Super Resolution Reconstruction) algorithms using median (L1) and mean (L2) filtering structures may degrade the reconstructed image sequence rather than enhance it. The mathematical analysis [1] demonstrates that the meridian filtering structure exhibits more robust characteristic...
This paper presents a Markov Random Field (MRF)-based approach for depth map super-resolution and enhancement. Given a low-resolution or moderate quality depth map, we study the problem of enhancing its resolution or quality with a registered high-resolution color image. Different from the previous methods, this MRF-based approach is based on a novel data term formulation that fits well to the unique...
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