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605 results about "Color contrast" patented technology

Image processing device, image processing method, program, storage medium and integrated circuit

It is an object to perform color correction that is simple and utilizes existing devices to achieve an increase in the feeling of depth in 2D images. Input image data are transformed into predetermined color information by a color information calculation portion 11. A correction amount control portion 10 determines a correction gain value for the color information according to depth information that has been input. A color information correction portion 12 performs color information correction based on the correction amount due to the contrast between the color information of a target pixel and representative color information of the surrounding region, and the correction gain value of the correction amount control portion. An output portion 13 converts this into a predetermined image format and outputs the result. Thus, by correcting the color information based on the contrast effect in conjunction with the depth information of the foreground and the background, for example, it is possible to easily increase the feeling of depth in a 2D image. Moreover, by controlling the color contrast effect with the depth information when performing the color correction, it becomes possible to more easily give a sense of depth that is perceived by humans.
Owner:SOVEREIGN PEAK VENTURES LLC

Image processing device, image processing method, image processing system, program, storage medium, and integrated circuit

The present invention executes color correction that improves the feeling of depth of a 2D image with ease and by using a preexisting device.
Input image data is first converted into brightness information by a brightness information calculation portion. The interest level within the image is then estimated by an interest level estimation portion based on that information. The vanishing point is then estimated by a vanishing point estimation portion. Next, a depth estimation portion estimates the degree of depth based on the distance from the vanishing point to a pixel i and the interest level of the pixel i, and calculates a depth correction gain value. A corrected image, obtained by controlling a depth correction image process based on the depth correction gain value, is converted to a predetermined image format and outputted by an output portion. Accordingly, by linking an interest level based on the brightness contrast/color contrast/blurriness amount with the depth estimation based on the vanishing point, the occurrence of abnormalities felt with images that do not properly match up with the perspective structure of the vanishing point, images that do not match the visual impression of humans, and so on can be reduced, making it possible to achieve a more natural and improved feeling of depth.
Owner:SOVEREIGN PEAK VENTURES LLC

Significant object detection method based on sparse subspace clustering and low-order expression

ActiveCN105574534ASolve the problem that it is difficult to detect large-scale salient objectsOvercome the difficulty of detecting large-scale saliency objects completely and consistentlyImage enhancementImage analysisGoal recognitionImage compression
The invention discloses a significant object detection method based on sparse subspace clustering and low-order expression. The method comprises the steps of: 1, carrying out super pixel segmentation and clustering on an input image; 2, extracting the color, texture and edge characteristics of each super pixel in clusters, and constructing cluster characteristic matrixes; 3, ranking all super pixel characteristics according to the magnitude of color contrast, and constructing a dictionary; according to the dictionary, constructing a combined low-order expression model, solving the model and decomposing the characteristic matrixes of the clusters so as to obtain low-order expression coefficients, and calculating significant factors of the clusters; and 5, mapping the significant value of each cluster into the input image according the spatial position, and obtaining a significant map of the input image. According to the invention, the significant objects relatively large in size in the image can be completely and consistently detected, the noise in a background is inhibited, and the robustness of significant object detection of the image with the complex background is improved. The significant object detection method is applicable to image segmentation, object identification, image restoration and self-adaptive image compression.
Owner:XIDIAN UNIV

Suspect vehicle inspection and control method and system

InactiveCN102610102ACheck and control fastEfficient investigation and controlRoad vehicles traffic controlCharacter and pattern recognitionTemplate matchingMaterial resources
The invention provides a suspect vehicle inspection and control method and system. The method comprises real-time acquiring a video stream and snap-shooting a vehicle image; subjecting the snap-shot image and a suspect vehicle sample image to color contrast to determine color similarity, and if the color similarity exceeds a set color similarity threshold, going to the next step; subjecting the snap-shot image and the suspect vehicle sample image to auxiliary characteristic contrast, to determine auxiliary characteristic similarity, the auxiliary characteristics including at least one of texture characteristics and shape characteristics; and comprehensively judging, and if the auxiliary characteristic similarity is larger than a set threshold, determining the comprehensive similarity by the auxiliary characteristic similarity or allowing the comprehensive similarity to depend on the auxiliary characteristic similarity. The vehicle image snap-shooting can be carried out by virtual coil triggering. Template match based on color can also be adopted to extract the auxiliary characteristics from a match region of the snap-shot image to be contrasted with the suspect vehicle sample image. The invention can realize rapid, efficient and accurate inspection and control effects, and save manpower and material resources.
Owner:SHANGHAI KEENSHINE ELECTRONIC TECH CO LTD

Natural sense color fusion method based on color contrast enhancement

The invention discloses a natural sense color fusion method based on color contrast enhancement, which includes that at the same time, a frame of optical registering grayscale image is respectively extracted from an infrared light video and a visible light video; linear operation is performed on the two frames of grayscale images, and the two frames of grayscale images are mapped to a luminosity ab (Lab) color space to obtain a pseudo-color fusion image of a two-waveband image, and a fused coefficient with optimal effect is selected by an observer; a group of pre-stored white light reference images is used for performing color transfer on the pseudo-color fusion image, and a reference image is selected by the observer; the selected reference image is used for performing natural sense color correction with the color contrast enhancement on the pseudo-color fusion image; and the reference image and the coefficient which are obtained in the previous step are used for performing rapid natural sense color fusion with the color contrast enhancement on the infrared light video and the visible light video. The fusion method can solve the problem that target and background color contrast of the natural sense color fusion of a two-waveband video is low in the prior art.
Owner:NANJING UNIV OF AERONAUTICS & ASTRONAUTICS

Object significance detecting method based on color contrast and color distribution

ActiveCN103136766APreserve edge detailFacilitate processing such as segmentationImage analysisPattern recognitionColor contrast
The invention provides an object significance detecting method based on color contrast and color distribution. The steps of the object significance detecting method based on the color contrast and the color distribution include that S1: an input image is divided into small size super-pixels, average color and position in the super-pixels are calculated; S2: the center-periphery color contrast of each super-pixel is calculated, the color contrast value is multiplied by a priori distribution, and at last color contrast significance diagram is obtained by using a significance smooth operation; S3: color distribution variance of each super-pixel is calculated, and thereby a color distribution significance diagram is obtained; S4: the color distribution significance diagrams obtained by the S2 and the S3 are multiplied and refined by using MeanShift division, edges of an object are enabled to be more fine, and the final significance diagram is output. According to the object significance detecting method based on the color contrast and the color distribution, the significance diagram obtained can evenly highlight the significant object in the significance diagram, the edge details of the object are well retained, the background interference is restrained, and the following up processes such as the target object division are benefited.
Owner:SHANGHAI JIAO TONG UNIV
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