Abstract: Techniques for complexity-adaptive and automatic two-dimensional (2D) to three-dimensional (3D) image and video conversion which classifies a frame of a 2D input into one of a flat image class and a non-flat image class are described. The flat image class frame is directly converted into 3D stereo for display. The frame that is classified as a non-flat image class is further processed automatically and adaptively, based on complexity, to create a depth map estimate. Thereafter, the non-flat image class frame is converted into a 3D stereo image using the depth map estimate or an adjusted depth map. The adjusted depth map is processed based on the complexity.

Abstract: Techniques for identifying and enhancing colors in a digital image associated with one or more target color shades. In an embodiment, the target color shades may include a shade of blue associated with the sky, a shade of green associated with outdoor foliage, or the color red. In an embodiment, the blue chroma (Cb) and red chroma (Cr) coordinates of a pixel are evaluated to determine whether to apply an enhancement factor. The enhancement factor may incorporate an exposure index (EI) auxiliary enhancement factor, a color temperature (D) auxiliary enhancement factor, and a luminance (Y) of each pixel. Further aspects for implementing the techniques in software and hardware are disclosed.

Abstract: Systems and methods of bad pixel cluster detection are disclosed. In a particular embodiment, a method includes determining a correlation value corresponding to a correlation coefficient between image data and at least one bad pixel cluster pattern, and detecting a bad pixel cluster corresponding to the at least one bad pixel cluster pattern based on the correlation value exceeding a threshold.

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: Systems and methods to selectively combine video frame image data are disclosed. First image data corresponding to a first video frame and second image data corresponding to a second video frame are received from an image sensor. The second image data is adjusted by at least partially compensating for offsets between portions of the first image data with respect to corresponding portions of the second image data to produce adjusted second image data. Combined image data corresponding to a combined video frame is generated by performing a hierarchical combining operation on the first image data and the adjusted second image data.

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: This disclosure describes an efficient architecture for an imaging device that supports image registration for still images and video coding of a video sequence. For image registration, the described architecture uses block-based comparisons of image blocks of a captured image relative to blocks of another reference image to support image registration on a block-by-block basis. For video coding, the described architecture uses block-based comparisons, e.g., to support for motion estimation and motion compensation. According to this disclosure, a common block comparison engine is used on a shared basis for both block-based image registration and block-based video coding. In this way, a hardware unit designed for block-based comparisons may be implemented so as to work in both the image registration process for still images and the video coding process for coding a video sequence.

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: A two-dimensional (2D) mesh is applied over a distortion surface to approximate a lens roll-off distortion pattern. The process to apply the 2D mesh distributes a plurality of grid points among the distortion pattern and sub-samples the distortion pattern to derive corrected digital gains at each grid location. Non-grid pixels underlying grid blocks having a grid point at each corner are adjusted based on the approximation of the lens roll-off for the grid points of the grid block. In one example, bilinear interpolation is used. The techniques universally correct lens roll-off distortion irregardless of the distortion pattern shape or type. The technique may also correct for green channel imbalance.

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: 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 example, 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, and the green pixels in blue rows are multiplied by the calibrated GB channel gain.

Abstract: The rendering of 3D video images on a stereo-enabled display (e.g., stereoscopic or autostereoscopic display) is described. The process includes culling facets facing away from a viewer, defining foreground facets for Left and Right Views and common background facets, determining lighting for these facets, and performing screen mapping and scene rendering for one view (e.g., Right View) using computational results for facets of the other view (i.e., Left View). In one embodiment, visualization of images is provided on the stereo-enabled display of a low-power device, such as mobile phone, a computer, a video game platform, or a Personal Digital Assistant (PDA) device.

Abstract: Briefly, in accordance with at least one embodiment, a technique for combining images to create or produce one or more optical effects is disclosed.

Abstract: Automatic white balance of captured images can be performed based on a gray world assumption. One aspect relates to an apparatus comprising a collection module and a processor. The collection module is configured to accumulate (a) red/green and blue/green color ratio values of a plurality of pixels in a captured image for each cluster of a plurality of clusters and (b) a number of pixels having red/green and blue/green color ratios associated with each cluster, the clusters comprising daylight, fluorescent, incandescent, and a outdoor green zone. The processor is configured to determine which cluster has a highest accumulated number of pixels, and use the cluster with the highest accumulated number of pixels to perform white balancing for the captured image.

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 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 is disclosed that includes receiving image data and calculating brightness information of the image data. The method includes correcting at least one lens roll-off value to be used in a lens roll-off correction operation based on the brightness information. The method also includes performing the lens roll-off correction operation on the image data using the at least one corrected lens roll-off value.

Abstract: Systems and methods to selectively combine video frame image data are disclosed. First image data corresponding to a first video frame and second image data corresponding to a second video frame are received from an image sensor. The second image data is adjusted by at least partially compensating for offsets between portions of the first image data with respect to corresponding portions of the second image data to produce adjusted second image data. Combined image data corresponding to a combined video frame is generated by performing a hierarchical combining operation on the first image data and the adjusted second image data.

Abstract: Implementations relate to systems and methods for real-time image recognition and mobile visual searching. A mobile device, such as a cellular phone, acquires an image and pre-processes the acquired image to generate a visual search query based on objects detected in the acquired image. The visual search query includes the acquired image or a query image extracted therefrom and metadata associated with the detected objects. The mobile device wirelessly communicates the visual search query to a remote server, and in response to the visual search query, the remote server recognizes an object in the query image based on the associated metadata. The remote server then generates information content based on the recognized object and communicates the information content to the mobile device to be presented via the mobile device.

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.