Showing papers on "Channel (digital image) published in 2009"

Single image haze removal using dark channel prior

Abstract: In this paper, we propose a simple but effective image prior - dark channel prior to remove haze from a single input image. The dark channel prior is a kind of statistics of the haze-free outdoor images. It is based on a key observation - most local patches in haze-free outdoor images contain some pixels which have very low intensities in at least one color channel. Using this prior with the haze imaging model, we can directly estimate the thickness of the haze and recover a high quality haze-free image. Results on a variety of outdoor haze images demonstrate the power of the proposed prior. Moreover, a high quality depth map can also be obtained as a by-product of haze removal.

System and method for analysis of light-matter interaction based on spectral convolution

Abstract: In embodiments of the present invention, systems and methods of a method and algorithm for creating a unique spectral fingerprint are based on the convolution of RGB color channel spectral plots generated from digital images that have captured single and/or multi-wavelength light-matter interaction.

System and method for generating a multi-dimensional image

Abstract: A system and method for generating a multi-dimensional image of an object in a scene is disclosed. One inventive aspect includes a spectral estimation module configured to convert a two-dimensional (2D) high-resolution light intensity image of the scene to a spectral-augmented image of a selected channel. The system further includes a high-resolution depth image generation module configured to generate a high-resolution depth image of the object based on a three-dimensional (3D) low-resolution depth image of the scene and the spectral-augmented image.

Extended depth-of-field using sharpness transport across color channels

Abstract: In this paper we present an approach to extend the Depth-of-Field (DoF) for cell phone miniature camera by concurrently optimizing optical system and post-capture digital processing techniques Our lens design seeks to increase the longitudinal chromatic aberration in a desired fashion such that, for a given object distance, at least one color plane of the RGB image contains the in-focus scene information Typically, red is made sharp for objects at infinity, green for intermediate distances, and blue for close distances Comparing sharpness across colors gives an estimation of the object distance and therefore allows choosing the right set of digital filters as a function of the object distance Then, by copying the high frequencies of the sharpest color onto the other colors, we show theoretically and experimentally that it is possible to achieve a sharp image for all the colors within a larger range of DoF We compare our technique with other approaches that also aim to increase the DoF such as Wavefront coding

Color extended visual cryptography using error diffusion

Abstract: This paper introduces a color visual cryptography encryption method that produces meaningful color shares via visual information pixel (VIP) synchronization and error diffusion halftoning. VIP synchronization retains the positions of pixels carrying visual information of original shares throughout the color channels and error diffusion generates shares pleasant to human eyes. Comparisons with previous approaches show the superior performance of the new method.

Color Based Bags-of-Emotions

Abstract: In this paper we describe how to include high level semantic information, such as aesthetics and emotions, into Content Based Image Retrieval. We present a color-based emotion-related image descriptor that can be used for describing the emotional content of images. The color emotion metric used is derived from psychophysical experiments and based on three variables: activity, weight and heat. It was originally designed for single-colors, but recent research has shown that the same emotion estimates can be applied in the retrieval of multi-colored images. Here we describe a new approach, based on the assumption that perceived color emotions in images are mainly affected by homogenous regions, defined by the emotion metric, and transitions between regions. RGB coordinates are converted to emotion coordinates, and for each emotion channel, statistical measurements of gradient magnitudes within a stack of low-pass filtered images are used for finding interest points corresponding to homogeneous regions and transitions between regions. Emotion characteristics are derived for patches surrounding each interest point, and saved in a bag-of-emotions, that, for instance, can be used for retrieving images based on emotional content.

Solid-state imaging apparatus, signal processing method of the same and imaging apparatus

Abstract: PROBLEM TO BE SOLVED: To reduce system costs by reducing required image memory capacity when attaining improvement in the sensitivity of brightness while suppressing reduction in color resolution. SOLUTION: Color coding of a color filter array 33A is determined to a checkered array wherein the RGB Bayer array is rotated at 45° with upper, lower, left and right neighboring four pixels in the same color, namely, RGB filters are square-arrayed for the unit of four pixels in the same color. Then, one microlens 34A is shared for the unit of four pixels (upper and lower two pixels × left and right two pixels) over different colors. COPYRIGHT: (C)2011,JPO&INPIT

Transferring color to grayscale images using vector quantization of luminance mapping techniques

Abstract: We develop an effective algorithm for colorizing a grayscale image In our approach, a reference color image, an RGB to color transform (=luminance, =chrominance), and a block-based vector quantization of luminance mapping (VQLM) technique are used to automatically colorize the grayscale image The VQLM technique compares the grayscale image with the luminance of the color reference image to obtain the information of the planes of the grayscale image After the chrominance is padded, the inverse color transform, to RGB, colorizes the grayscale scene is colorized Meanwhile, we create a mean of VQLM (MVQLM) method to improve the quality of the colorized grayscale image Experimental results show the MVQLM method is better than the VQLM method Also, we investigate colorizing the grayscale image working in the and YIQ spaces The simulation results also reveal that working in the space is slightly better than working in the YIQ space Compared to other colorizing schemes, our proposed method has two advantages: 1 the codebook and MVQLM techniques colorize the grayscale images for any size image that can be evenly divided by 2 automatically; and 2 the MVQLM method obtains a smoother colorizing effect and improved quality compared to the VQLM method

Dual projection system with inversely synchronized channel projections

Abstract: A dual projection system utilizes a first projector and a second projector to project alternating left and right channel images of a 3D display. The projectors are inversely synchronized such that while the first projector projects a right channel image the other projector projects a left channel image. A projection filter in each projector has left channel properties when the image being projected is a left channel image and right channel properties when the image being projected is a right channel image. The images projected from each projector alternate between left and right channel images approximately once per frame.

Registration and Enhancement of Double-Sided Degraded Manuscripts Acquired in Multispectral Modality

Abstract: We propose a system to process multispectral scans of double-sided documents. It can co-register any number of recto and verso channel maps, and reduce the bleed-through/show-through distortions by exploiting blind source separation. From RGB scans, it is also able to recover the original colors, thus improving the readability of a document while maintaining its original appearance. The recto and verso patterns obtained can then be further analyzed. Many approaches to this problem are based on single-channel or multichannel recto-verso scans. In any case, getting rid of the unwanted interferences is a challenging problem. All the methods relying on pixel intensities, such as the one presented here, need a very accurate co-registration, and this is difficult for recto-verso pairs since the relevant information is often very sparse.

Digital broadcast receiving method providing two-dimensional image and 3d image integration service, and digital broadcast receiving device using the same

Abstract: A digital broadcast receiving apparatus for providing an integrated service of a 2D image and a 3D image comprises: a demultiplexing unit configured to demultiplex a received digital broadcast signal; a PSIP or PSI/SI processor configured to extract at least any one of 3D service information related to a 2D image channel or service and 2D service information related to a 3D image channel or service from the demultiplexed digital broadcast signal; a decoder configured to decode an extension view video stream and a base view video stream from the demultiplexed digital broadcast signal; and an output formatting unit configured to format the extension view video stream and the base view video stream based on at least any one of the 3D service information and the 2D service information. When a selection of the 3D image service is input by a user, a 3D image channel or service providing a 3D image with respect to the 2D image channel or service based on the 3D service information may be selected, and when a selection of the 2D image service is input by the user, a 2D image channel or service providing a 2D image with respect to the 3D image channel or service based on the 2D service information may be selected. Accordingly, an integrated service of a 2D image and a 3D image can be provided in a digital broadcast.

Wi-fi sensor

Abstract: Disclosed is a combined spectrum and channel analyzer with output in the form of various graphical displays. The graphical displays can be configured to display frequency, amplitude, time and density via a spectral view, a topographic view, or a planar view, or combinations of those views. Channel activities, parameters, overlap and interaction are shown in the displays.

Color gamut scalability techniques

Abstract: Techniques are described that can be used to either compress or expand video. Color compression techniques are described that can be used to compress the wide color gamut content into lower color gamut for inclusion in a baseline layer. Color expansion techniques are described that convert lower color gamut data into wider color gamut format for inclusion in an enhancement layer. Both of the baseline video stream and enhancement layer video streams may be transmitted through a channel or stored in a memory device to be viewed later. Accordingly, both baseline and enhancement video layers are available so that either lower or higher quality displays can be used to display video.

A Channel Coding Approach for Human Authentication From Gait Sequences

Abstract: Human authentication using biometric traits has become an increasingly important issue in a large range of applications. In this paper, a novel channel coding approach for biometric authentication based on distributed source coding principles is proposed. Biometric recognition is formulated as a channel coding problem with noisy side information at the decoder and error correcting codes are employed for user verification. It is shown that the effective exploitation of the noise channel distribution in the decoding process improves performance. Moreover, the proposed method increases the security of the stored biometric templates. As a case study, the proposed framework is employed for the development of a novel gait recognition system based on the extraction of depth data from human silhouettes and a set of discriminative features. Specifically, gait sequences are represented using the radial and the circular integration transforms and features based on weighted Krawtchouk moments. Analytical models are derived for the effective modeling of the correlation channel statistics based on these features and integrated in the soft decoding process of the channel decoder. The experimental results demonstrate the validity of the proposed method over state-of-the-art techniques for gait recognition.

Apparatus and method for improving image quality of image sensor

Abstract: Provided are an apparatus and method for improving an image quality of an image sensor, capable of adaptively removing noise occurring in a de-mosaicking that is performed for generating three-channel data of R, G and B from a single channel pixel structure based on a bayer pattern. The apparatus includes a first converting unit for converting RGB color data into a YCbCr color data, the RGB color data being obtained from bayer data through a de-mosaicking, a noise removal unit for removing noise from a Cb and a Cr color data outputted from the first converting unit, and a second converting unit for converting the Cb and the Cr color data from the noise removal unit and a Y data from the first converting unit into the RGB color data.

New digital camera sensor architecture for low light imaging

Abstract: In this paper, a novel digital camera sensor architecture to acquire images with high fidelity under low light conditions is proposed. Today, almost all digital cameras have only red, green, and blue color pixels. Due to their limited sensitivity to the wavelengths of visible light, the images captured using these color pixels under low light conditions are noisy. A new sensor architecture that has panchromatic pixels sensitive to all visible wavelengths along with the red, green, and blue pixels is proposed. Panchromatic pixels allow luminance information to be detected with higher sensitivity whereas red, green, and blue pixels produce the color information. Real images captured using the proposed sensor design are compared with the corresponding images obtained using a traditional digital camera having only red, green, and blue pixels. The results clearly show the feasibility of the proposed approach.

Color Correction by Estimation of Dominant Chromaticity in Multi-Scaled Retinex

Abstract: In image capture a scene with nonuniform illumination has an influence on the image quality, especially the contrast and detail in dark regions. Generally, the tone curve or histogram of an image is modified to improve the contrast and detail, yet this is in- sufficient as the intensity and chromaticity of the illumination vary with geometric position. Thus, the multi-scaled retinex algorithm has been proposed, where the influence of nonuniform illumination is reduced by partitioning the original image using local average im- ages that are estimated based on Gaussian filtering of the original image. However, the multi-scaled retinex algorithm produces color distortion as the local average images are independently estimated for each channel. In particular, if the chromatic distribution of the original image is not uniform and is dominated by a certain chroma- ticity, the local average image includes not only the intensity and chromaticity of the illumination but also the dominant chromaticity through the Gaussian filtering, thereby distorting the color. Accord- ingly, this article proposes a multi-scaled retinex using a modified local average image to reduce the color distortion by the dominant chromaticity of the original image. As with the multi-scaled retinex algorithm, the local average image is obtained through Gaussian filtering of the original image. The local average image is then di- vided by the average chromaticity value of the original image to reduce the influence of the dominant chromaticity. However, be- cause the average chromaticity value includes the dominant chro- maticity of the original image and the chromaticity of the illumination, the chromaticity removed from the illumination in the local average image needs to be compensated. Therefore, the chromaticity of the illumination is estimated based on the chromaticity of the highlight regions in the original image. The chromaticity of the local average image is then modified by the estimated chromaticity. In experi- ments, the proposed method was found to improve local contrast and reduce the color distortion. © 2009 Society for Imaging Science and Technology. DOI: 10.2352/J.ImagingSci.Technol.2009.53.5.050502

Watermarking of colour images in the DCT domain using Y channel

Abstract: In this paper an image authentication technique that embeds a binary watermark into a host color image is proposed. In this scheme the colour image is first transformed from the RGB to the YCbCr color space. The watermark is embedded into the Y channel of the host image by selectively modifying the very low frequency parts of the DCT transformation. It is shown that the proposed technique can resist classical attacks such as JPEG Compression, low pass filtering, median filtering, cropping, and geometrical scaling attack. Moreover, the recovery method is blind and doesn't need the original host image for extraction.

A novel image authentication scheme based on hyper-chaotic cell neural network

Abstract: This paper presents a new image authentication scheme based on cell neural network with hyper-chaos characteristics (HCCNN). In the scheme, the authentication code, which is used as secret key and the pixel values of image are used for the input of HCCNN. The secret information that HCCNN produces is transmitted to the receiving end through secret channel. The receiver can then use the received secret information to authenticate the suspect image by comparing the original authentication code with that calculated from the suspect image. Simulations show that the suggested image authentication algorithm has the advantages of large key space and high security, and moreover, it can detect and locate the position of any slightly tampered parts of a suspect image.

Single image defogging

Abstract: Bad weather, such as fog and haze can significantly degrade the visibility of a scene. In order to overcome it, some approaches have been proposed. In this paper, we proposed a novel defogging algorithm just based on a single image. Firstly, we employ the method of dark channel prior as a foundation of our algorithm. After experimental analysis about the dark channel prior haze removal, we find that although dark channel prior behaves well in most situations, it also results in larger saturation values in some specific situations. Then, focusing on these situations, we propose an iterative algorithm to adjust the color distortion effected by higher saturation. Actually, this kind of global or local rectification can achieve a relatively ideal compromise between natural color and image definition. Experiments show that the algorithm proposed in this paper is good at dealing with the similarity-to-atmospheric-light objects defogging problem.

An Enhanced Statistical Approach to Identifying Photorealistic Images

Abstract: Computer graphics identification has gained importance in digital era as it relates to image forgery detection and enhancement of high photorealistic rendering software. In this paper, statistical moments of 1-D and 2-D characteristic functions are employed to derive image features that can well capture the statistical differences between computer graphics and photographic images. YCbCr color system is selected because it has shown better performance in computer graphics classification than RGB color system and it has been adopted by the most popularly used JPEG images. Furthermore, only Y and Cb color channels are used in feature extraction due to our study showing features derived from Cb and Cr are so highly correlated that no need to use features extracted from both Cb and Cr components, which substantially reduces computational complexity. Concretely, in each selected color component, features are extracted from each image in both image pixel 2-D array and JPEG 2-D array (an 2-D array consisting of the magnitude of JPEG coefficients), their prediction-error 2-D arrays, and all of their three-level wavelet subbands, referred to as various 2-D arrays generated from a given image in this paper. The rationale behind using prediction-error image is to reduce the influence caused by image content. To generate image features from 1-D characteristic functions, the various 2-D arrays of a given image are the inputs, yielding 156 features in total. For the feature generated from 2-D characteristic functions, only JPEG 2-D array and its prediction-error 2-D array are the inputs, one-unit-apart 2-D histograms of the JPEG 2-D array along the horizontal, vertical and diagonal directions are utilized to generate 2-D characteristic functions, from which the marginal moments are generated to form 234 features. Together, the process then results in 390 features per color channel, and 780 features in total Finally, Boosting Feature Selection (BFS) is used to greatly reduce the dimensionality of features while boosts the machine learning based classification performance to fairly high.

Stereo Picture Quality Estimation Based on a Multiple Channel HVS Model

Abstract: The understanding and estimation of stereo images are very important. There are many models of human visual system for planar image. It is blank for stereo image. An estimation of stereo image quality is proposed based on a multiple channel human visual system (HVS) for use in image compression .The model is based on a plane model, but has some modifications that make it is more suitable to stereo image pair. Difference as the important characteristic of stereo images is used to evaluate the quality of stereo image.

Modifying color and panchromatic channel cfa image

Abstract: A method of modifying a CFA image or full-color image having a plurality of color channels and a panchromatic channel, includes capturing the panchromatic channel at a different exposure time than at least one of the color image channels with the CFA sensor within one image; producing a panchromatic edge map and a color edge map from the CFA image; using the panchromatic edge map and the color edge map to provide motion estimates; and using the motion estimates to modify at least one of the channels of the CFA image or full-color image.

A reduced-reference video structural similarity metric based on no-reference estimation of channel-induced distortion

Abstract: The reduced-reference (RR) approximation of a full-reference (FR) video quality assessment method is a convenient way to build evaluation metrics which are both intrinsically well correlated with human judgments and feasible to implement in a network scenario, without the need to explore the perceptual significance of new video features through mean opinion score tests. In this paper, we propose a RR approximation of the video structural similarity index (VSSIM), a FR metric which is known to be well descriptive of the video quality perceived by users. We focus on the visual degradation produced by channel transmission errors: first, at the encoder, a small set of salient structural video features is assembled and transmitted through the RR channel to the end-user; then, at the decoder the feature vector is combined with a fine-granularity, no-reference estimate of the channel-induced distortion to produce the VSSIM approximation. By uniformly quantizing the feature vector and compressing it using a context-adaptive, variable length encoder, we show that good correlation coefficients with ground-truth VSSIM (ρ = 0.85) may be achieved spending, respectively, less than 12 and 27 kbps for a video sequence with CIF or SD resolution.

A DCT Domain Color Watermarking Scheme Based on Chaos and Multilayer Arnold Transformation

Abstract: A novel DCT domain color digital watermarking scheme based on chaotic maps is proposed, and the host image is color RGB image. The color space of the color host image is first converted from RGB to YIQ. In order to resist JPEG compression, all three watermark RGB channel signals are buried to Y component of the YIQ color space host images. In the proposed method, the image watermark is embedded into low-band DCT coefficients with different strength according to the characteristics of human vision system. The watermark signal and the embedding position of the host image are encrypted respectively by the unified chaotic map and multilayer Arnold cat map, and compared with the general Arnold cat map, the key space is highly increased. The simulation results show that the proposed scheme possesses the invisibility and the robustness to common image processing attacks, such as noise addition, JPEG compression, image rotation, cutting and so on.