Showing papers on "Channel (digital image) published in 2007"

Retinal Blood Vessel Segmentation Using Line Operators and Support Vector Classification

Abstract: In the framework of computer-aided diagnosis of eye diseases, retinal vessel segmentation based on line operators is proposed. A line detector, previously used in mammography, is applied to the green channel of the retinal image. It is based on the evaluation of the average grey level along lines of fixed length passing through the target pixel at different orientations. Two segmentation methods are considered. The first uses the basic line detector whose response is thresholded to obtain unsupervised pixel classification. As a further development, we employ two orthogonal line detectors along with the grey level of the target pixel to construct a feature vector for supervised classification using a support vector machine. The effectiveness of both methods is demonstrated through receiver operating characteristic analysis on two publicly available databases of color fundus images.

Color Image Denoising via Sparse 3D Collaborative Filtering with Grouping Constraint in Luminance-Chrominance Space

Abstract: We propose an effective color image denoising method that exploits filtering in highly sparse local 3D transform domain in each channel of a luminance-chrominance color space. For each image block in each channel, a 3D array is formed by stacking together blocks similar to it, a process that we call "grouping". The high similarity between grouped blocks in each 3D array enables a highly sparse representation of the true signal in a 3D transform domain and thus a subsequent shrinkage of the transform spectra results in effective noise attenuation. The peculiarity of the proposed method is the application of a "grouping constraint" on the chrominances by reusing exactly the same grouping as for the luminance. The results demonstrate the effectiveness of the proposed grouping constraint and show that the developed denoising algorithm achieves state-of-the-art performance in terms of both peak signal-to-noise ratio and visual quality.

Image sensor with improved light sensitivity

Abstract: An image sensor for capturing a color image is disclosed having a two-dimensional array having first and second groups of pixels wherein pixels from the first group of pixels have narrower spectral photoresponses than pixels from the second group of pixels and wherein the first group of pixels has individual pixels that have spectral photoresponses that correspond to a set of at least two colors, with the placement of the first and second groups of pixels defining a pattern that has a minimal repeating unit including at least six pixels with at least some rows or columns of the minimal repeating unit composed only of pixels from the second group of pixels, and including ways to combine similarly positioned pixels from at least two adjacent minimal repeating units.

Quantitative image analysis of immunohistochemical stains using a CMYK color model

Abstract: Computer image analysis techniques have decreased effects of observer biases, and increased the sensitivity and the throughput of immunohistochemistry (IHC) as a tissue-based procedure for the evaluation of diseases. We adapted a Cyan/Magenta/Yellow/Key (CMYK) model for automated computer image analysis to quantify IHC stains in hematoxylin counterstained histological sections. The spectral characteristics of the chromogens AEC, DAB and NovaRed as well as the counterstain hematoxylin were first determined using CMYK, Red/Green/Blue (RGB), normalized RGB and Hue/Saturation/Lightness (HSL) color models. The contrast of chromogen intensities on a 0–255 scale (24-bit image file) as well as compared to the hematoxylin counterstain was greatest using the Yellow channel of a CMYK color model, suggesting an improved sensitivity for IHC evaluation compared to other color models. An increase in activated STAT3 levels due to growth factor stimulation, quantified using the Yellow channel image analysis was associated with an increase detected by Western blotting. Two clinical image data sets were used to compare the Yellow channel automated method with observer-dependent methods. First, a quantification of DAB-labeled carbonic anhydrase IX hypoxia marker in 414 sections obtained from 138 biopsies of cervical carcinoma showed strong association between Yellow channel and positive color selection results. Second, a linear relationship was also demonstrated between Yellow intensity and visual scoring for NovaRed-labeled epidermal growth factor receptor in 256 non-small cell lung cancer biopsies. The Yellow channel image analysis method based on a CMYK color model is independent of observer biases for threshold and positive color selection, applicable to different chromogens, tolerant of hematoxylin, sensitive to small changes in IHC intensity and is applicable to simple automation procedures. These characteristics are advantageous for both basic as well as clinical research in an unbiased, reproducible and high throughput evaluation of IHC intensity.

Assessment of High Speed Imaging Systems for 2D and 3D Deformation Measurements: Methodology Development and Validation

Abstract: Ultra high-speed and moderate speed image acquisition platforms have been characterized, with special emphasis on the variability and accuracy of the measurements obtained when employed in either 2D or 3D computer vision systems for deformation and shape measurements. Specifically, the type of image distortions present in both single channel cameras (HS-CMOS) and multi-channel image intensified cameras (UHS-ICCD) are quantified as part of the overall study, and their effect on the accuracy of experimental measurements obtained using digital image correlation have been determined. Results indicate that established methods for noise suppression and recently developed models for distortion correction can be used effectively in situations where the primary intensity noise components are characterized by minimal cross-talk and stationary spatial distortions. Baseline uniaxial tension experiments demonstrate that image correlation measurements using high speed imaging systems are unbiased and consistent with independent deformation measurements over the same length scale, with point-to-point strain variations that are similar to results obtained from translation experiments. In this study, the point-to-point variability in strain using the image intensified system is on the order of 0.001, whereas the non-intensified system had variability of 0.0001. Results confirm that high speed imaging systems can be utilized for full field two and three-dimensional measurements using digital image correlation methods.

System And Method For Camera Imaging Data Channel

Abstract: A system and method for using cameras to download data to cell phones or other devices as an alternative to CDMA/GPRS, BlueTooth, Infrared or cable connections. The data is encoded as a sequence of images such as 2D bar codes, which can be displayed in any flat panel display, acquired by a camera, and decoded by software embedded in the device. The decoded data is written to a file. The system and method meet the following challenges: (1) To encode arbitrary data as a sequence of images. (2) To process captured images under various lighting variations and perspective distortions while maintaining real time performance. (3) To decode the processed images robustly even when partial data is lost.

Apparatus and Methods for Encoding, Decoding and Representing High Dynamic Range Images

Abstract: A data structure defining a high dynamic range image comprises a tone map having a reduced dynamic range and HDR information. The high dynamic range image can be reconstructed from the tone map and the HDR information. The data structure can be backwards compatible with legacy hardware or software viewers. The data structure may comprise a JFIF file having the tone map encoded as a JPEG image with the HDR information in an application extension or comment field of the JFIF file, or a MPEG file having the tone map encoded as a MPEG image with the HDR information in a video or audio channel of the MPEG file. Apparatus and methods for encoding or decoding the data structure may apply pre- or post correction to compensate for lossy encoding of the high dynamic range information.

Flux Tensor Constrained Geodesic Active Contours with Sensor Fusion for Persistent Object Tracking.

Abstract: This paper makes new contributions in motion detection, object segmentation and trajectory estimation to create a successful object tracking system. A new efficient motion detection algorithm referred to as the flux tensor is used to detect moving objects in infrared video without requiring background modeling or contour extraction. The flux tensor-based motion detector when applied to infrared video is more accurate than thresholding ”hot-spots”, and is insensitive to shadows as well as illumination changes in the visible channel. In real world monitoring tasks fusing scene information from multiple sensors and sources is a useful core mechanism to deal with complex scenes, lighting conditions and environmental variables. The object segmentation algorithm uses level set-based geodesic active contour evolution that incorporates the fusion of visible color and infrared edge informations in a novel manner. Touching or overlapping objects are further refined during the segmentation process using an appropriate shapebased model. Multiple object tracking using correspondence graphs is extended to handle groups of objects and occlusion events by Kalman filter-based cluster trajectory analysis and watershed segmentation. The proposed object tracking algorithm was successfully tested on several difficult outdoor multispectral videos from stationary sensors and is not confounded by shadows or illumination variations.

Learning to compress images and videos

Abstract: We present an intuitive scheme for lossy color-image compression: Use the color information from a few representative pixels to learn a model which predicts color on the rest of the pixels. Now, storing the representative pixels and the image in grayscale suffice to recover the original image. A similar scheme is also applicable for compressing videos, where a single model can be used to predict color on many consecutive frames, leading to better compression. Existing algorithms for colorization -- the process of adding color to a grayscale image or video sequence -- are tedious, and require intensive human-intervention. We bypass these limitations by using a graph-based inductive semi-supervised learning module for colorization, and a simple active learning strategy to choose the representative pixels. Experiments on a wide variety of images and video sequences demonstrate the efficacy of our algorithm.

Color Reproduction From Noisy CFA Data of Single Sensor Digital Cameras

Abstract: Single sensor digital color still/video cameras capture images using a color filter array (CFA) and require color interpolation (demosaicking) to reconstruct full color images. The color reproduction has to combat sensor noises which are channel dependent. If untreated in demosaicking, sensor noises can cause color artifacts that are hard to remove later by a separate denoising process, because the demosaicking process complicates the noise characteristics by blending noises of different color channels. This paper presents a joint demosaicking-denoising approach to overcome this difficulty. The color image is restored from noisy mosaic data in two steps. First, the difference signals of color channels are estimated by linear minimum mean square-error estimation. This process exploits both spectral and spatial correlations to simultaneously suppress sensor noise and interpolation error. With the estimated difference signals, the full resolution green channel is recovered. The second step involves in a wavelet-based denoising process to remove the CFA channel-dependent noises from the reconstructed green channel. The red and blue channels are subsequently recovered. Simulated and real CFA mosaic data are used to evaluate the performance of the proposed joint demosaicking-denoising scheme and compare it with many recently developed sophisticated demosaicking and denoising schemes.

Region-based super-resolution for compression

Abstract: Every user of multimedia technology expects good image and video visual quality independently of the particular characteristics of the receiver or the communication networks employed. Unfortunately, due to factors like processing power limitations and channel capabilities, images or video sequences are often downsampled and/or transmitted or stored at low bitrates, resulting in a degradation of their final visual quality. In this paper, we propose a region-based framework for intentionally introducing downsampling of the high resolution (HR) image sequences before compression and then utilizing super resolution (SR) techniques for generating an HR video sequence at the decoder. Segmentation is performed at the encoder on groups of images to classify their blocks into three different types according to their motion and texture. The obtained segmentation is used to define the downsampling process at the encoder and it is encoded and provided to the decoder as side information in order to guide the SR process. All the components of the proposed framework are analyzed in detail. A particular implementation of it is described and tested experimentally. The experimental results validate the usefulness of the proposed method.

Image stabilization using multi-exposure pattern

Abstract: The specification and drawings present a new method, apparatus and software product for image stabilization of an image taken with a fixed (i.e., pre-selected) multi-exposure pattern for at least one color channel by an image sensor of a camera, wherein a plurality of groups of pixels of the image sensor have different pre-selected exposure times for said at least one color channel. The camera can be a part of, e.g., an electronic device such as mobile phone or a portable electronic device.

Correlation between Brightness and Channel Currents of Electrical Discharges

Abstract: Channel brightness of 500 mm long electrical discharges were measured by analyzing a set of digitized images taken by 3 cameras placed symmetrically around a discharge gap at a radial distance of 200 cm from the axis of the spark. The sparks were generated between a steel rod and a plane electrode. The distribution of the brightness across the channel represented a Gaussian distribution. A linear correlation was seen between the channel brightness measured by different cameras looking at the same spark channel. No correlation was seen between the channel brightness and the channel depth (direction perpendicular to the camera plane). The measured peak current and the brightness of the main spark channel show a high degree of correlation (R2=0.97). The sum of brightness of branches was equal to the brightness of the parent channel. One can use this result to calculate the relative distribution of branch currents in complex electrical discharges including natural lightning flashes. If the current in the parent channel is known, branch currents can be calculated by measuring the optical intensities using photographic techniques.

Method and apparatus for determining expected distortion in decoded video blocks

Abstract: There are provided methods and apparatus for determining expected distortion in decoded video blocks. An apparatus includes a distortion calculator (1050) for calculating an expected distortion for an image block, included in a picture of a video sequence and sent over a lossy channel, using a motion vector for the image block when the motion vector has a non-integer value. The distortion calculator (1050) calculates the expected distortion based upon a propagated distortion of at least two neighboring integer pixel positions in a reference picture with respect to the motion vector having the non-integer value. The image block is coded in an inter mode or a SKIP mode.

Multispectral MRI De-noising Using Non-Local Means.

Abstract: Clinical MRI data is normally corrupted by random noise from the measurement process which reduces the accuracy and reliability of any automatic analysis. For this reason, de-noising methods are often applied to increase the SNR and improve image quality. Most of these methods work on single channel images by correcting each grey level using an implicit model of the surrounding region, but without taking into consideration the potential multispectral nature of MR images. In this paper we present an extension of a recently proposed filter to reduce random noise in multispectral MR images and test it on synthetic and real images. We compare performance to a multispectral approach based upon the imaging physics and published previously at this conference using real data. We conclude from our results that these methods can be used for de-noising of MR data.

An embedded saliency map estimator scheme: application to video encoding.

Abstract: In this paper we propose a novel saliency-based computational model for visual attention. This model processes both top-down (goal directed) and bottom-up information. Processing in the top-down channel creates the so called skin conspicuity map and emulates the visual search for human faces performed by humans. This is clearly a goal directed task but is generic enough to be context independent. Processing in the bottom-up information channel follows the principles set by Itti et al. but it deviates from them by computing the orientation, intensity and color conspicuity maps within a unified multi-resolution framework based on wavelet subband analysis. In particular, we apply a wavelet based approach for efficient computation of the topographic feature maps. Given that wavelets and multiresolution theory are naturally connected the usage of wavelet decomposition for mimicking the center surround process in humans is an obvious choice. However, our implementation goes further. We utilize the wavelet decomposition for inline computation of the features (such as orientation angles) that are used to create the topographic feature maps. The bottom-up topographic feature maps and the top-down skin conspicuity map are then combined through a sigmoid function to produce the final saliency map. A prototype of the proposed model was realized through the TMDSDMK642-0E DSP platform as an embedded system allowing real-time operation. For evaluation purposes, in terms of perceived visual quality and video compression improvement, a ROI-based video compression setup was followed. Extended experiments concerning both MPEG-1 as well as low bit-rate MPEG-4 video encoding were conducted showing significant improvement in video compression efficiency without perceived deterioration in visual quality.

A Color Watermarking Scheme Based on Block-SVD and Arnold Transformation

Abstract: This paper proposes a color watermarking scheme based on block-SVD and Arnold transformation. Color watermark means more meaningful information could be concealed in host image. Block-SVD has faster speed than SVD algorithm. We can adjust the block size according to the amount of the watermark to be embedded. Watermark's pixel is buried to the maximum singular value (SV) bit of each block obtained from the block-SVD transformation of host image in each RGB channel. In order to enhance the security and the resistance to image cropping of the scheme, Arnold transformation is applied to watermark scrambling pretreatment. Experimental results show robustness of the proposed scheme against common image processing operations, such as Gaussian noise addition, low pass filtering, lossy JPEG compression, rescaling, cropping and so on.

Visual and infrared dual-band false color image fusion method motivated by Land’s experiment

Abstract: A new false color image fusion method is proposed on the basis of Land's experiment on color constancy of human vision, through idealized hypothesis of the red filter and green filter, through equienergy distribution hypothesis of the light source, and by relating the infrared and visual images to the black-and-white transparencies obtained through the red and green filters of Land's experiment, respectively. The normalization of each color channel conforms with the von Kries chromatic adaptation model and the maximum red-green-blue method, which has been popularly adopted in some video systems and color theories to estimate the illumination color and which, to a certain extent, agrees with the color constancy of human vision. The method has been proven effective after it was compared with Toet et al.'s fusion method. Its colorfulness is enhanced by the strategy of assigning the difference between the source images to the blue channel, which is used in Toet et al.'s algorithm to underscore the characteristic components of the individual images. The additional opponent processing neurodynamic equation of the center-surround receptive field can improve the output contrast significantly and is believed to be more suitable for revealing details by human observers. Some perceptual evaluation results are also given at the end.

Method and apparatus for providing 3D still image service over digital broadcasting

Abstract: A method and apparatus for providing 3D still image service in a specific time interval during audio-visual service of digital broadcast are provided. The method includes receiving a reference image and a 3D supplement image, which construct a 3D still image, through a data channel or a video channel together with a 2D image; restoring the reference image and the 3D supplement image to the 3D still image; and displaying the 3D still image in a specific interval during digital audio-visual broadcast using the 2D image according to display information which includes a play time and a play mode.

Two way communication system

Abstract: A two-way communication system for viewers at first and second sites, including an integrated imaging apparatus at the first site for displaying second site images from the second site while capturing first site images from the first site and sending them over a channel to a second site; a structure at the second site coupled to the channel and responsive to images from the integrated imaging apparatus to display such first site images and capturing second site images sending them over the channel to the integrated imaging apparatus; wherein the integrated imaging apparatus, includes, an electronic display having an array of display pixels in which at least one display pixel is partially transparent; and at least one image capture device which is operably associated with the partially transparent pixel.

Chromatic aberration correction

Abstract: A chromatic aberration (CA) correction technique is presented that substantially removes CA from an image captured by a digital camera. In general, the effects of any in-camera sharpening are reversed by applying a blurring kernel. The image is then super-sampled to approximate its state prior to the application of in-camera sampling. One of the color channels is designated as a reference channel, and an objective function is established for each of the non-reference channels. The reference color channel is assumed to be CA-free, while the objective functions are used to compute the unknown CA parameters for each non-reference channel. These sets are used in a CA removal function to substantially remove the CA associated with each of the non-reference channels. The image is then sampled to return it to its original resolution, and a sharpening filter is applied if needed to undo the effects of the previously applied blurring kernel.

Image Enhancement Using Elastic Manifolds

Abstract: Image denoising and enhancement problems have many physical analogues that highlight new approaches to novel solutions. One such solution, based on viewing the image as elastic sheet, is presented. A processing scheme for grayscale images is outlined and further considered in the context of color images. Preliminary analysis and simulations on noisy images indicate that multidimensional manifold representation of combined space-color information incorporates the advantages of separate color channel representations. Experimental analysis reveals elastic sheet method to be a powerful and robust denoising tool, which preserves most meaningful details.

Method and apparatus for identifying facial regions

Abstract: An apparatus and method for identifying facial regions in an image includes a computer running a program that tests pixel values of an image to identify objects therein having attributes like pupils, such as shape, size, position and reflectivity. To reduce the time to identify pupils, the image is sub-rected, sub-sampled and only one color/brightness channel is tested.

Dual-channel PCNN and Its Application in the Field of Image Fusion

Abstract: Image fusion plays an important role in many fields such as computer vision, medical image, manufacturing, military, and remote sensing so on. Pulse coupled neural network (PCNN) is derived from the synchronous neuronal burst phenomena in the cat visual cortex. So it is very suitable for image processing. Due to some defects of original PCNN for data fusion, we propose a novel PCNN model - dual- channel PCNN for the first time based on original model, which is specialized in image fusion. In order to explain efficiency and validity of our proposed method, we take two medical images for example to explain further the advantages in comparison to other image fusion methods. Better results are obtained with our approach. Our fused image includes more information than others, which show our method is better and efficient one. Meanwhile our method not only fuses multi-source images very well but also enhances the quality of the fused image.

POCS-Based Restoration of Bayer-Sampled Image Sequences

Abstract: Spatial resolution of digital images are limited due to optical/sensor blurring and sensor site density. In single-chip digital cameras, the resolution is further degraded because such devices use a color filter array to capture only one spectral component at a pixel location. The process of estimating the missing two color values at each pixel location is known as demosaicking. Demosaicking methods usually exploit the correlation among color channels. When there are multiple images, it is possible not only to have better estimates of the missing color values but also to improve the spatial resolution further (using super-resolution reconstruction). Previously, we have proposed a demosaicking algorithm based on the projection onto convex sets (POCS) technique. In this paper, we improve the results of that algorithm adding a new constraint set based on the spatio-intensity neighborhood. We extend the algorithm to image sequences for multi-frame demosaicking and super resolution.

Maximum a posteriori estimation of spectral reflectance from color image and multipoint spectral measurements

Abstract: Accurate color image reproduction under arbitrary illumination can be realized if the spectral reflectance functions in a scene are obtained. Although multispectral imaging is one of the promising methods to obtain the reflectance of a scene, it is expected to reduce the number of color channels without significant loss of accuracy. This paper presents what we believe to be a new method for estimating spectral reflectance functions from color image and multipoint spectral measurements based on maximum a posteriori (MAP) estimation. Multipoint spectral measurements are utilized as auxiliary information to improve the accuracy of spectral reflectance estimated from image data. Through simulations, it is confirmed that the proposed method improves the estimation accuracy, particularly when a scene includes subjects that belong to various categories.

Hybrid sampling approach for imaging Fourier-transform spectrometry

Abstract: A new approach to interferogram sampling is demonstrated for Fourier-transform spectrometry. Sampling of the infrared channel is triggered at equidistant optical path differences while samples are time-referenced with a high-resolution digital clock. This hybrid method exploits the advantages of both time and position-sampling techniques. It minimizes the dataload while allowing a postcorrection scheme to remove sampling errors. It is therefore highly adapted to imaging spectrometers designed for massively parallel spatial sampling. Also, this technique is particularly interesting for spectrometers equipped with an integrating detector, such as a CCD camera, since it can account for the inevitable delay caused by camera integration.

Detection of facial characteristics based on edge information

Abstract: In this paper, a novel method for eye and mouth detection and eye center and mouth corner localization, based on geometrical information is presented. First, a face detector is applied to detect the facial region, and the edge map of this region is extracted. A vector pointing to the closest edge pixel is then assigned to every pixel. x and y components of these vectors are used to detect the eyes and mouth. For eye center localization, intensity information is used, after removing unwanted effects, such as light reflections. For the detection of the mouth corners, the hue channel of the lip area is used. The proposed method can work efficiently on low-resolution images and has been tested on the XM2VTS database with very good results.

Method and device for the creation of pseudo-holographic images

Abstract: A method and a device enable the creation of three-dimensional images with more than two perspectives (e.g. pseudo-holographic images), especially to be reproduced with the aid of an autostereoscopic display or an autostereoscopic screen, from fed images having, in particular, only two perspectives, e.g., a left and a right image channel. Also, a related device creates and reproduces three-dimensional images having more than two perspectives, especially in the form of an autostereoscopic multi-user visualization system.