Described herein are methods and systems for texturing a three-dimensional (3D) model using photogrammetry. A sensor captures scans of a physical object, including related pose information, and color images corresponding to each scan. A computing device generates a 3D mesh of the physical object. The computing device preprocesses the color images to remove blurry images and detect textured regions of the object in each non-blurry image. The computing device optimizes the pose information for each color image by generating associations between the color images and vertices in the 3D mesh and classifying the vertices as textured or non-textured. The computing device generates texture coordinates for the 3D mesh by segmenting the mesh, parameterizing the segments, and packing the parameterized segments into a texture atlas. The computing device paint the texture atlas using the color images that have optimized pose information to generate a model having texture coordinates for each vertex.

The current document is directed to a computationally efficient method and system for assessing the suitability of a text-containing digital image for various types of computational image processing, including optical-character recognition. A text-containing digital image is evaluated by the disclosed methods and systems for sharpness or, in other words, for the absence of, or low levels of, noise, optical blur, and other defects and deficiencies. The sharpness-evaluation process uses computationally efficient steps, including convolution operations with small kernels to generate contour images and intensity-based evaluation of pixels within contour images for sharpness and proximity to intensity edges in order to estimate the sharpness of a text-containing digital image for image-processing purposes.

An image processing apparatus to execute noise reduction processing on image data includes a setting unit, a determination unit, and an output unit. The setting unit sets a pixel group from among a plurality of pixel group candidates. The plurality of pixel group candidates includes at least a first pixel group having a plurality of pixels being a first number of pixels or a second pixel group having a plurality of pixels being a second number of pixels which is different from the first number of pixels. The determination unit determines, based on a similarity between a target pixel and a reference pixel that is obtained according to the set pixel group, a weight corresponding to the reference pixel. The output unit outputs a value, calculated based on a pixel value of the reference pixel and the weight, as a noise-reduced pixel value of the target pixel.

The present invention discloses an image adaptive noise reduction method and a device thereof. The method includes: dividing an original image into a plurality of sub-blocks; performing a space conversion for all the sub-blocks; performing a significance analysis to obtain a significant characteristic map; performing a threshold segmentation on all the significant characteristic maps by a significant standard value to obtain a significant characteristic region and a non-significant characteristic region; performing adaptive filtering on the significant characteristic region and maxing an original image in the non-significant characteristic region to obtain a mixed image; and performing an image space inverse conversion for the mixed image, and outputting a final image. The present invention uses the method of dividing the image, based on the significant characteristics of the image, reducing noise reduction in the non-significant characteristic region, saving algorithm running time and hardware resources.

The present disclosure relates to an apparatus and method for optimizing inverse tone mapping on basis of a single image to reconstruct into a high quality High Dynamic Range (HDR) image using a Low Dynamic Range (LDR) image and a recording medium for performing the method, and includes inputting a LDR image to Inverse Tone Mapping (ITM) operator, inputting a result value by the ITM operator to Tone Mapping (TM) operator, comparing a result value by the TM operator with a threshold for HDR luminance determination, and selecting the result value by the TM operator which is smaller than the threshold as an HDR image.

Methods and systems for denoising a digital image are provided. The method includes determining first and second plurality of pixel patches including respective first (p) and second (q) pixels, determining a patch distance between each pair of corresponding pixel patches in the first plurality and the second plurality of pixel patches, determining an effective distance between the first pixel (p) and the second pixel (q), repeating the above steps for the same first pixel (p) and another second pixel (q) until a predetermined number of pixels (q) in the raw digital image is processed, and then denoising the first pixel (p), including determining respective contributions of the pixels (q) into a noise reduction of the pixel (p), using respective effective distances of the pixels (q). A corresponding system is also provided. Embodiments of the invention provide computational advantages for denoising digital images.

A method for applying a filter to data to improve data quality and/or reduce file size. In one example, a region of interest of an image is identified. A histogram is generated of pixel intensity values in the region of interest. The histogram is iteratively updated to focus (zoom) in on the highest peak in the histogram. A Gaussian curve is fitted to the updated histogram. A bilateral filter is applied to the images, where parameters of the bilateral filter are based on the parameters of the Gaussian curve.

Systems and methods for local tone mapping are provided. In one example, an electronic device includes an electronic display, an imaging device, and an image signal processor. The electronic display may display images of a first bit depth, and the imaging device may include an image sensor that obtains image data of a higher bit depth than the first bit depth. The image signal processor may process the image data, and may include local tone mapping logic that may apply a spatially varying local tone curve to a pixel of the image data to preserve local contrast when displayed on the display. The local tone mapping logic may smooth the local tone curve applied to the intensity difference between the pixel and another nearby pixel exceeds a threshold.

Systems and methods are provided for upsampling low temporal resolution depth maps. This upsampling is performed by obtaining a stereo pair of images of a scene captured at a first timepoint, generating a first depth map of the scene for the first timepoint by performing stereo matching on the stereo pair of images, obtaining a subsequent stereo pair of images captured at a subsequent timepoint to the first timepoint, and generating a subsequent depth map that corresponds to the subsequent timepoint by applying an edge-preserving filter using the first depth map without performing stereo matching on the subsequent stereo pair of images.

Systems and methods for a user to paint an image includes generating a display of a room image uploaded by the user are provided and include The systems and methods include employing a straight-line masking tool to block off a first area of the room image with a straight line such that color will not be applied to the first area when color is applied to a second area of the room image. The systems and methods also include employing a polygon masking tool to draw at least three lines to mask off a selected polygon area of the room image such that color can be applied by the user to an inside of the selected polygon area when the user selects the inside of the selected polygon area and an outside of the selected polygon area when the user selects the outside of the selected polygon area.