437results about How to "Improve image processing capabilities" patented technology

The present invention relates to a multi-energy system that generates and/or forms images of targets/structures by applying Mueller matrix imaging principles and/or Stokes polarimetric parameter imaging principles to data obtained by the multi-energy system. In one embodiment, the present invention utilizes at least one energy or light source to generate two or more Mueller matrix and/or Stokes polarization parameters images of a target/structure, and evaluates the Mueller matrix/Stokes polarization parameters multi-spectral difference(s) between the two or more images of the target/structure. As a result, high contrast, high specificity images can be obtained. Additional information can be obtained by and/or from the present invention through the application of image, Mueller matrix decomposition, and/or image reconstruction techniques that operate directly on the Mueller matrix and/or Stokes polarization parameters.

Devices and methods for assessing the size, shape, and topography of vessel lumens and hollow portions of organs are described. The devices and methods are particularly adapted for determining the size, shape, topography, and compliance of the native heart valves to facilitate the later implantation of a prosthetic heart valve. The devices are typically catheter-based having an assessment mechanism fixed to a distal end of the catheter. The assessment mechanism generally includes an expandable member, such as a balloon. The assessment mechanism may also include an imaging member, a physical assessment member, an electronic mapping construction, an alignment mechanism, a valvuloplasty balloon, or any combinations thereof. The methods typically comprise deploying the balloon percutaneously to a target location, expanding the balloon, and determining one or more physical parameters associated with the target location.

A digital camera is provided for generating a manipulated output image. The camera focuses an image using an automatic focusing technique thereby generating focus settings. The focus settings are stored in a memory of the digital camera and used in manipulating the captured image to produce an enhanced image. The digital image manipulation process is selected from the group consisting of applying a face detection algorithm to the captured focussed image and producing a painting effect within the captured focussed image.

A flying vehicle guiding system, which comprises a remotely controllable flying vehicle system, a surveying instrument being able to measure distance, angle, and track, and a ground base station for controlling a flight of the flying vehicle system based on measuring results by the surveying instrument, wherein the flying vehicle system has a retro-reflector as an object to be measured, wherein the surveying instrument has a non-prism surveying function for performing distance measurement and angle measurement without a retro-reflector, a prism surveying function for performing distance measurement and angle measurement with respect to the retro-reflector, and a tracking function for tracking the retro-reflector and for performing distance measurement and angle measurement, wherein the surveying instrument performs non-prism measurement on a scheduled flight area, the ground base station sets a safe flight area based on the results of the non-prism measurement, and controls so that the flying vehicle system flies in the safe flight area based on the results of tracking measurement by de surveying instrument.

A method of processing a digital image comprising: capturing the image utilizing an adjustable focusing technique; utilizing the focusing settings as an indicator of the position of structures within the image; and processing the image, utilizing the said focus settings to produce effects specific to said focus settings.

An optical component is connectable to a camera unit and comprises a data structure including data associated with the optical component. When the optical component is connected to the camera unit, data associated with the optical component is transferred to the camera unit. Image production of an organ by the camera unit is controlled based on the data associated with the optical component.

A method for processing high dynamic range (HDR) images by selecting preferred tone mapping operators and gamut mapping algorithms based on scene classification. Scenes are classified into indoor scenes, outdoor scenes, and scenes with people, and tone mapping operators and gamut mapping algorithms are selected on that basis. Prior to scene classification, the multiple images taken at various exposure values are fused into a low dynamic range (LDR) image using an exposure fusing algorithm, and scene classification is performed using the fused LDR image. Then, the HDR image generated from the multiple images are tone mapped into a LDR image using the selected tone mapping operator and then gamut mapped to the color space of the output device such as printer.

A printing system enables the printing of enhanced documents using a semantic classification scheme. A printing system receives an image to be printed. The system classifies the image according to the semantic classification scheme and, based on this classification, performs enhancement processing on the image. Depending on the desired application, the printing system may recognize and classify any number of image types and may then perform various enhancement processing functions on the image, where the type of enhancement processing performed is based on the classification of the image.

An image processor generates a Super-Resolution (SR) frame by upscaling. A Human Visual Preference Model (HVPM) helps detect random texture regions, where visual artifacts and errors are tolerated to allow for more image details, and immaculate regions having flat areas, corners, or regular structures, where details may be sacrificed to prevent annoying visual artifacts that seem to stand out more. A regularity or isotropic measurement is generated for each input pixel. More regular and less anisotropic regions are mapped as immaculate regions. Higher weights for blurring, smoothing, or blending from a single frame source are assigned for immaculate regions to reduce the likelihood of generated artifacts. In the random texture regions, multiple frames are used as sources for blending, and sharpening is increased to enhance details, but more artifacts are likely. These artifacts are more easily tolerated by humans in the random texture regions than in the regular-structure immaculate regions.

A subject area extracting unit extracts a main-subject area from the color image data; a correction amount calculating unit calculates a gradation correction amount based on the information on the thus-extracted main-subject area; a control zone extracting unit extracts a predetermined control zone from a brightness zone to which the main-subject area does not belongs; a determining unit determines whether or not the gradation correction amount on the control zone should be controlled, according to a predetermined control requirement; and a control unit controls the gradation correction amount according to the determination result of the determination unit.

A medical tracking system includes a tracking unit including an image recording and image signal processing system, and a programmable computer platform integrated with the tracking unit. The programmable computer platform includes a navigation unit configured to implement at least part of medical navigation.

The present invention relates to an antistatic article comprising a substrate or support having thereon at least one antistatic layer, wherein the antistatic layer comprises a conductive material having areas of patterned coverage.

In an aspect of an image processing technique according to the present invention, a high-frequency component is extracted from a low-resolution image z which is a restoration target, and a high-frequency image z′ is generated (#20). Interpolation filter coefficients A′_i, B′_i and π_i and a representative high-frequency image z′_i are set (#22), a

Gaussian mixture model represented by x=Σ{((A′_i×z′)+B′_i)×w_i((z′_i−z′), π_i)} is assumed and a filtering process is applied to the high-frequency image z′ (#24). On the other hand, an enlargement process is applied to a low-frequency component and a medium-frequency component of the low-resolution image z (#26), a processing result of the filtering process and a processing result of the enlargement process are added (#28), and a high-resolution image is restored.

An image processing apparatus is provided for enhancing the image processing function without having to increase the circuit scale. The image processing apparatus includes an image divider, a pixel processor, and an image coupler. If the number of horizontal pixels on the width of an input image is larger than a size of a line buffer, the image divider equally divides the input image in the vertical direction so that the resulting divided area is smaller than the number of horizontal pixels on the width of the line buffer. Then, the image divider controls an input data transfer circuit so that the pixel data of the input image may be sequentially transferred to the line buffer for each of the equally divided areas. The image processor sequentially processes the pixel data of the input image temporarily stored in the line buffer and then sends out the output pixel data. The image coupler controls the output data transfer circuit so that the output pixel data sequentially outputted for one divided area may be coupled with the output pixel for another divided area, for generating the output image.

The invention relates to the technical field of image detection, and especially relates to a TFT-LCD lighting automatic optical inspection based image processing method. The image processing method comprises the following steps: acquiring images of a display screen in different modes; preprocessing the acquired images to remove the background interference; carrying out mask treatment on the preprocessed images; and carrying out defect extraction and calculation. The TFT-LCD lighting automatic optical inspection based image processing method uses a plurality of automatic optical inspection modes, can realize the normal detection of spot, line and Mura defects, and can realize the accurate positioning of light spot and light line defects to a sub-pixel, and the classification of the Mura defects according to an SEMU criterion. The image processing method has the advantages of simple flow, and effective ensure of the detection rate.

The invention provides an image processing system. In one embodiment, the image processing system comprises a first camera, a second camera, a depth map generator, and an automatic focusing module. The first camera generates a first image. The second camera generates a second image. The depth map generator generates a depth map comprising information about visual shift between the first image and the second image. The automatic focusing module estimates a distance between a target object and a center position between the first camera and the second camera, and adjusts the focusing lengths of the first camera and the second camera according to the estimated distance.