Abstract: A monoscopic low-power mobile device is capable of creating real-time stereo images and videos from a single captured view. The device uses statistics from an autofocusing process to create a block depth map of a single capture view. Artifacts in the block depth map are reduced and an image depth map is created. Stereo three-dimensional (3D) left and right views are created from the image depth map using a Z-buffer based 3D surface recover process and a disparity map which is a function of the geometry of binocular vision.

Abstract: An apparatus comprising a first image sensor, a second image sensor spaced apart from the first image sensor, a diversity combine module to combine image data from the first and second image sensors, and an image processing module configured to process combined image data from the diversity combine module.

Abstract: A mobile device comprising a first image sensor, a second image sensor configured to change position with respect to the first image sensor, a controller configured to control the position of the second image sensor, and an image processing module configured to process and combine images captured by the first and second image sensors.

Abstract: Methods and apparatus for processing a captured image of a medium, content on the medium, and a background surrounding the medium are provided. A captured image is processed by 1) improving the visibility of the content by recovering the original appearance of the medium and enhancing the appearance of the content image, 2) removing the background by determining the boundary of the medium, and/or 3) correcting geometric distortion in the content to improve readability. Any of the three processing steps may be used alone or any combination of the three processing steps may be used to process the image. The image processing may operate on the image after it is captured and stored to a memory and may be implemented on an image-capturing device that captures the image. In other embodiments, the image processing is implemented on another device that receives the image from the image-capturing device.

Abstract: A method and apparatus for down scaling image data is disclosed. One method controls a phase for an M/N filter, where N represents a number of input samples, and M represents a number of output samples. N is greater than M. Another method may switch between an M/N filter and a phase-controlled M/N filter.

Abstract: A digital image system identifies defective pixels of a digital image sensor based on sensor values of pixels positioned in at least two dimensions on the digital image sensor. The exemplary imaging system includes a buffer for receiving sensor values that are each associated with a pixel in the digital image sensor and electronics for comparing the sensor value associated with a test pixel to the sensor values of pixels positioned in at least two dimensions on the digital image sensor. The electronics determines whether the test pixel is a defective pixel based on the comparison.

Abstract: This disclosure describes adaptive filtering techniques to improve the quality of captured imagery, such as video or still images. In particular, this disclosure describes adaptive filtering techniques that filter each pixel as a function of a set of surrounding pixels. An adaptive image filter may compare image information associated with a pixel of interest to image information associated with a set of surrounding pixels by, for example, computing differences between the image information associated with the pixel of interest and each of the surrounding pixels of the set. The computed differences can be used in a variety of ways to filter image information of the pixel of interest. In some embodiments, for example, the adaptive image filter may include both a low pass component and high pass component that adjust as a function of the computed differences.

Abstract: This disclosure describes adaptive filtering techniques to improve the quality of captured imagery, such as video or still images. In particular, this disclosure describes adaptive filtering techniques that filter each pixel as a function of a set of surrounding pixels. An adaptive image filter may compare image information associated with a pixel of interest to image information associated with a set of surrounding pixels by, for example, computing differences between the image formation associated with the pixel of interest and each of the surrounding pixels of the set. The computed differences can be used in a variety of ways to filter image information of the pixel of interest. In some embodiments, for example, the adaptive image filter may include both a low pass component and high pass component that adjust as a function of the computed differences.

Abstract: This disclosure describes adaptive filtering techniques to improve the quality of captured imagery, such as video or still images. In particular, this disclosure describes adaptive filtering techniques that filter each pixel as a function of a set of surrounding pixels. An adaptive image filter may compare image information associated with a pixel of interest to image information associated with a set of surrounding pixels by, for example, computing differences between the image information associated with the pixel of interest and each of the surrounding pixels of the set. The computed differences can be used in a variety of ways to filter image information of the pixel of interest. In some embodiments, for example, the adaptive image filter may include both a low pass component and high pass component that adjust as a function of the computed differences.

Abstract: A method and apparatus for adaptive green channel odd-even mismatch removal to effectuate the disappearance of artifacts caused by the odd-even mismatch in a demosaic processed image. In one adaptive approach, a calibrated GR channel gain for red rows and a calibrated GB channel gain for blue rows are determined and are a function of valid pixels only in each respective region. After the calibration, in a correction process, the green pixels in red rows of a region are multiplied by the calibrated GR channel gain. On the other hand, the green pixels in blue rows are multiplied by the calibrated GB channel gain. Thus, after demosaic processing, the corrected image has essentially no artifacts caused by odd-even mismatch of the green channel. Alternately, the adaptive green channel odd-even mismatch removal method replaces the center green pixel of a region having an odd number of columns and rows with a normalized weighted green pixel sum total.

Abstract: The imaging system converts raw data for an image to formatted data concurrently with compressing the formatted data for the image. The exemplary imaging system includes an image processor for generating blocks of formatted data from raw image data. The exemplary imaging system also includes an image compressor for compressing the blocks of formatted data. The compressor compresses one or more of the blocks while the image processor generates one or more blocks of formatted data.

Abstract: This disclosure describes video encoding techniques and video encoding devices that implement such techniques. In one embodiment, this disclosure describes a video encoding device comprising a motion estimator that computes a motion vector predictor based on motion vectors previously calculated for video blocks in proximity to a current video block to be encoded, and uses the motion vector predictor in searching for a prediction video block used to encode the current video block, and a motion compensator that generates a difference block indicative of differences between the current video block to be encoded and the prediction video block.