Abstract: A system for the identification of feature points in low contrast images.

Abstract: A method for image processing includes determining edge pixels of a model image and determining features for the edge pixels of the model image. The image processing includes determining edge pixels of an input image and determining features for the edge pixels of the input image. The system matches the features of the model image with the features of the input image to determine candidate locations of an object within the input image.

Abstract: A computer-implemented method for enhancing an input image that includes modifying the relatively lower frequency aspects of the input image based upon a brightening process, where the brightening process is based upon a brightening selection which is based upon a combination of an under brightening term and a clipping term and a joint saturation boost and brightening. The method modifies the relatively higher frequency aspects of the input image based upon reducing lower amplitude noise and enhancing the noise reduced higher frequency aspects of the input image, and combines the modified relatively lower frequency aspects of the input image and the modified relatively higher frequency aspects of the input image.

Abstract: A technique for image processing that includes receiving a model image, an input image, and registering the input image with the model image. A modified input image is determined that includes a first component that is substantially free of error components with respect to the model image and a second component that is substantially free of non-error aspects with respect to the model image. The technique determines an improved alignment of the modified input image with the model image where the improved alignment and the first and second components are determined jointly.

Abstract: A system for detecting newton ring mura on a display includes sensing an image of the display with an image capture device and determining a border boundary of an illuminated portion of the display. The image is spatially filtered as defined by the border boundary using a filter that reduces sensor noise and a grid pattern of the display. The spatially filtered image is processed to determine if a region proximate a pixel location is a potential newton ring mura defect and characterizing the potential newton ring mura defects to remove at least one of the potential newton ring mura defects.

Abstract: A system for image processing includes determining edge pixels of a model image using an edge based technique and determining an angular orientation for each the edge pixels of the model image. The system determines a histogram of gradient orientations based upon the angular orientations of the model image. The system determining edge pixels of an input image using an edge based technique and determining an angular orientation for each of the edge pixels of the input image. The system determines a histogram of gradient orientations based upon the angular orientations of the input image. The system compares the histogram of gradient orientations of the model image with the histogram of gradient orientations of the input image to determine candidate locations of an object within the input image.

Abstract: A system for improving content visibility on a display under low-contrast viewing conditions using an image process technique.

Abstract: An electronic device configured for defect detection is described. The electronic device includes a processor and instructions stored in memory that is in electronic communication with the processor. The electronic device performs background suppression on the image data based on a transform of the image data to obtain a score map. The electronic device also applies thresholding to the score map to generate a detection mask. The thresholding comprises bi-thresholding. The electronic device additionally detects any defects based on the detection mask. The electronic device further indicates any defects.

Abstract: A system for image processing includes determining edge pixels of a model image using an edge based technique and determining an angular orientation for each the edge pixels of the model image. The system determines a histogram of gradient orientations based upon the angular orientations of the model image. The system determining edge pixels of an input image using an edge based technique and determining an angular orientation for each of the edge pixels of the input image. The system determines a histogram of gradient orientations based upon the angular orientations of the input image. The system compares the histogram of gradient orientations of the model image with the histogram of gradient orientations of the input image to determine candidate locations of an object within the input image.

Abstract: A method for scaling an image includes providing a set of filters based upon a low-resolution data set and a high-resolution data set suitable for up-scaling a low resolution image to a high resolution image. The filters are collectively representative of at least a portion of an image space and a substantial number of the filters are representative of a different at least one selected from a volume and a shape within the image space. A low-resolution image is received and generates a corresponding high-resolution image based up the filters.

Abstract: A system for modification of an image to be displayed on a display includes receiving an input image and adjusting a luminance level for a backlight of the display for displaying the input image based upon an ambient lighting level and a visual system responsive model to the ambient lightening level.

Abstract: A system for improving content visibility on a display under low-contrast viewing conditions using an image process technique.

Abstract: A system for improving content visibility on a display under low-contrast viewing conditions.

Abstract: A system for improving content visibility on a display under low-contrast viewing conditions using an image separation technique.

Abstract: A method for image processing includes determining edge pixels of a model image and determining features for the edge pixels of the model image. The image processing includes determining edge pixels of an input image and determining features for the edge pixels of the input image. The system matches the features of the model image with the features of the input image to determine candidate locations of an object within the input image.

Abstract: A method for image processing that includes determining edge pixels of a model image using an edge based technique, and an angular orientation for each of the edge pixels of the model image. The method determines a lower spatial resolution model image based upon the model image and determining respective angular orientations for the lower spatial resolution model image. The method determines edge pixels of an input image using an edge based technique, and an angular orientation for each of the edge pixels of the input image. The method determines a lower spatial resolution input image based upon the input image and determining respective angular orientations for the lower spatial resolution input image. The method matches the lower spatial resolution model image with the lower spatial resolution input image to determine candidate locations of an object within the input image and based upon the candidate locations matching the input image with the model image.

Abstract: An electronic device configured for defect detection is described. The electronic device includes a processor and instructions stored in memory that is in electronic communication with the processor. The electronic device performs background suppression on the image data based on a transform of the image data to obtain a score map. The electronic device also applies thresholding to the score map to generate a detection mask. The thresholding comprises bi-thresholding. The electronic device additionally detects any defects based on the detection mask. The electronic device further indicates any defects.

Abstract: A system for detecting newton ring mura on a display includes sensing an image of the display with an image capture device and determining a border boundary of an illuminated portion of the display. The image is spatially filtered as defined by the border boundary using a filter that reduces sensor noise and a grid pattern of the display. The spatially filtered image is processed to determine if a region proximate a pixel location is a potential newton ring mura defect and characterizing the potential newton ring mura defects to remove at least one of the potential newton ring mura defects.

Abstract: A system for image processing includes determining edge pixels of a model image using an edge based technique, and an angular orientation for each of the edge pixels of the model image. The system determines a lower spatial resolution model image based upon the model image and determining respective angular orientations for the lower spatial resolution model image, and determines edge pixels of an input image using an edge based technique, and an angular orientation for each of the edge pixels of the input image. The system determines a lower spatial resolution input image based upon the input image and determining respective angular orientations for the lower spatial resolution input image, and matches the lower spatial resolution model image with the lower spatial resolution input image to determine candidate locations of an object within the image and based upon the candidate locations matching the input image with the model image.

Abstract: A system for identifying a repair cut location for a defect in a liquid crystal device includes receiving an input image, a defect mask image, and a landmark structure image. The system determines a repair cut location, based upon the input image, the defect mask image, and the landmark structure image, for a liquid crystal device proximate the defect. The determination may be based upon a type of said defect, a cause of said defect, a position of said defect, and a spatial relationship of the defect and a structure of the landmark image.