Abstract: A method includes detecting, based on sensor data from a sensor on a mobile device, an environmental brightness measurement, where the mobile device comprises a display screen configured to adjust display brightness based on environmental brightness. The method further includes determining, based on image data from a camera on the mobile device, an extent to which the detected environmental brightness measurement is caused by reflected light from the display screen. The method additionally includes setting a rate of exposure change for the camera based on the determined extent to which the detected environmental brightness measurement is caused by reflected light from the display screen.

Abstract: A method includes detecting, based on sensor data from a sensor on a mobile device, an environmental brightness measurement, where the mobile device comprises a display screen configured to adjust display brightness based on environmental brightness. The method further includes determining, based on image data from a camera on the mobile device, an extent to which the detected environmental brightness measurement is caused by reflected light from the display screen. The method additionally includes setting a rate of exposure change for the camera based on the determined extent to which the detected environmental brightness measurement is caused by reflected light from the display screen.

Abstract: A method includes detecting, based on sensor data from a sensor on a mobile device, an environmental brightness measurement, where the mobile device comprises a display screen configured to adjust display brightness based on environmental brightness. The method further includes determining, based on image data from a camera on the mobile device, an extent to which the detected environmental brightness measurement is caused by reflected light from the display screen. The method additionally includes setting a rate of exposure change for the camera based on the determined extent to which the detected environmental brightness measurement is caused by reflected light from the display screen.

Abstract: The invention relates to methods and devices for mitigating and/or minimizing effects of hand jitter or shaking during an auto-focusing process of an image-capturing device. In order to more accurately focus a lens for capturing a digital image, the lens is moved between a minimum and maximum position (along an axis) while capturing sample image frames using a focus window at various lens positions. Improved auto-focusing is achieved by dynamically adjusting the relative position of the focus window for each image frame to cover substantially the same image portion of the target image. By adjusting the focus window for each image frame to cover substantially the same image portion of the target image, variations from shaking may be minimized, thereby improving auto-focusing.

Abstract: A method and device are provided for mitigating and/or minimizing effects of hand jitter or shaking during an auto-focusing process of an image-capturing device. In order to more accurately focus a lens for capturing a digital image, the lens is moved between a minimum and maximum position (along an axis) while capturing sample image frames using a focus window at various lens positions. Improved auto-focusing is achieved by dynamically adjusting the relative position of the focus window for each image frame to cover substantially the same image portion of the target image. By adjusting the focus window for each image frame to cover substantially the same image portion of the target image, variations from shaking may be minimized, thereby improving auto-focusing.

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 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: An imaging system generates a gain for a component of an image format. The gain is at least partially dependent on the brightness of the light source illuminating a scene when an image of the scene was generated. The gain can be used to correct the component of the image format for the color shift in the image caused by the light source. In some instances, the imaging system generates a gain for a plurality of the components of the image format or for all of the components of the image format. The gains can be used to correct the components for the color shift in the image caused by the light source.

Abstract: A method of processing an image includes selecting, for each of a plurality of picture element values in at least a portion of the image, one among a plurality of offset values. For each of the plurality of picture element values, an index value is obtained based on (A) the selected offset value and (B) a portion of the picture element value. For each of the plurality of picture element values, an entry is retrieved from a lookup table according to the corresponding index value.

Abstract: An adaptive filter according to one embodiment includes an N×N two-dimensional convolution, where N is an odd integer greater than one. Pixels of an image are filtered by moving the N×N kernel across the image. At each pixel location, the kernel coefficients are determined by the image pixels within the N×N region, such that the kernel coefficients may change from one pixel location to the next. Such a filter may be implemented to use a lookup table to approximate a floating-point operation.

Abstract: Brightness and color tone shift distortion of captured images by a non-ideal lens can be compensated by applying an inverse transfer function to the captured image. An estimate of the lens transfer function can be measured based on a radius from a center of the lens. The lens transfer function can be measured by capturing a flat field image. The center of the lens can be determined based on a relative brightness maximum. The relative brightness of the captured flat field image can then be measured as a function of radius to generate a lens response curve. Separate response curves can be measured for each color component. A correction curve can be determined as the inverse of the response curve. The correction curve can be applied to subsequent captured images to compensate for lens degradation.

Abstract: Automatic white balance of captured images can be performed based on a gray world assumption. Initially, a flat field gray image is captured for one or more reference illuminations. The statistics of the captured gray image are determined and stored for each reference illumination during a calibration process. For each subsequent captured image, the image is filtered to determine a subset of gray pixels. The gray pixels are further divided into a one or more gray clusters. The average weight of the one or more gray clusters is determined and a distance from the average weights to the reference illuminants is determined. An estimate of the illuminant is determined depending on the distances. White balance gains are applied to the image based on the estimated illuminant.