Abstract: This disclosure describes techniques for improving functionalities of a video encoder, using parameters detected and estimated by a front-end video capture device. The techniques may involve estimating a blurriness level associated with frames captured during a refocusing process. Based on the estimated blurriness level, the quantization parameter (QP) used to encode blurry frames is adjusted either in the video capture device or in the video encoder. The video encoder uses the adjusted QP to encode the blurry frames. The video encoder also uses the blurriness level estimate to adjust encoding algorithms by simplifying motion estimation and compensation in the blurry frames.

Abstract: This disclosure describes techniques for improving functionalities of a back-end device, e.g., a video encoder, using parameters detected by a front-end device, e.g., a video camera. The techniques may involve detecting a scene change in a captured frame, based on one or more parameters of auto exposure (AE), auto white balance (AWB), and auto focus (AF) functions. If a scene change is detected in a captured frame, a video processing device, which may be a stand-alone device, or may be integrated into one of the front-end or back-end devices, provides an indication of the scene change. The video encoder interprets the signal as a trigger to encode the frame indicated as the frame where a scene change occurred as a reference I frame.

Abstract: A method for adjusting parameters in a video capture device using motion information is disclosed. Motion information that indicates motion of a video capture device is determined. The motion information is compared to an upper bound and a lower bound. An aggressiveness level that indicates a change in a white balance gain for the video capture device is determined based on the comparison. A new white balance gain for the video capture device is determined based on the aggressiveness level. An exposure convergence holding time is adjusted based on the motion information. An exposure step size is increased based on the motion information. A brightness level of the video capture device is adjusted based on the convergence step size.

Abstract: An apparatus and method of processing images is disclosed. In a particular embodiment, the method includes receiving a selection of a first image from a plurality of images stored at a memory device and displaying the first image. The method also includes receiving image modification data to modify processing of the first image displayed and providing an adjusted value of an image processing parameter to an image processor. The adjusted value of the image processing parameter is determined based at least in part on the image modification data.

Abstract: A system and method of image capture parameter adjustment using face brightness information is disclosed. In a particular embodiment, a method is disclosed that includes determining a luma value based on a brightness variation within a selected portion of an image, where the selected portion of the image corresponds to at least a portion of a face. The method further includes adjusting an image capture parameter at least partially based on the determined luma value.

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: In a particular embodiment, a method is disclosed that includes comparing a frame rate of image capture by an image sensor to a frame rate threshold at an image capture device. The method also includes when the frame rate is less than the frame rate threshold, increasing the frame rate to a modified frame rate that is greater than or at least equal to the frame rate threshold. The method further includes performing an autofocus operation on an image to be captured at the modified frame rate.

Abstract: In a particular embodiment, a method is disclosed that includes determining at least one ambient exposure parameter using an ambient illumination, the at least one ambient exposure parameter including a first sensitivity parameter of an autoexposure controller using the ambient illumination. The method includes determining at least one low-illumination parameter using a first lamp level, the at least one low-illumination parameter including a second sensitivity parameter of the autoexposure controller using the first lamp level, where the autoexposure controller is configured to operate according to at least one high-illumination parameter based on the at least one ambient exposure parameter and the at least one low-illumination parameter. The method further includes performing an image capture operation using a second lamp level that is brighter than the first lamp level, where the at least one high-illumination parameter includes a third sensitivity parameter.

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 techniques for improving functionalities of a back-end device, e.g., a video encoder, using parameters detected and estimated by a front-end device, e.g., a video camera. The techniques may involve estimating a blurriness level associated with frames captured during a refocusing process. Based on the estimated blurriness level, the quantization parameter (QP) used to encode blurry frames is adjusted either in the video camera or in the video encoder. The video encoder uses the adjusted QP to encode the blurry frames. The video encoder also uses the blurriness level estimate to adjust encoding algorithms by simplifying motion estimation and compensation in the blurry frames.

Abstract: This disclosure describes techniques for improving functionalities of a back-end device, e.g., a video encoder, using parameters detected by a front-end device, e.g., a video camera. The techniques may involve detecting a scene change in a captured frame, based on one or more parameters of auto exposure (AE), auto white balance (AWB), and auto focus (AF) functions. If a scene change is detected in a captured frame, a video processing device, which may be a stand-alone device, or may be integrated into one of the front-end or back-end devices, provides an indication of the scene change. The video encoder interprets the signal as a trigger to encode the frame indicated as the frame where a scene change occurred as a reference I frame.

Abstract: An apparatus and method of processing images is disclosed. In a particular embodiment, the method includes receiving a selection of a first image from a plurality of images stored at a memory device and displaying the first image. The method also includes receiving image modification data to modify processing of the first image displayed and providing an adjusted value of an image processing parameter to an image processor. The adjusted value of the image processing parameter is determined based at least in part on the image modification data.

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: A system and method of image capture parameter adjustment using face brightness information is disclosed. In a particular embodiment, a method is disclosed that includes determining a luma value based on a brightness variation within a selected portion of an image, where the selected portion of the image corresponds to at least a portion of a face. The method further includes adjusting an image capture parameter at least partially based on the determined luma value.

Abstract: A method for adjusting parameters in a video capture device using motion information is disclosed. Motion information that indicates motion of a video capture device is determined. The motion information is compared to an upper bound and a lower bound. An aggressiveness level that indicates a change in a white balance gain for the video capture device is determined based on the comparison. A new white balance gain for the video capture device is determined based on the aggressiveness level. An exposure convergence holding time is adjusted based on the motion information. An exposure step size is increased based on the motion information. A brightness level of the video capture device is adjusted based on the convergence step size.

Abstract: In a particular embodiment, a method is disclosed that includes receiving image data at an auto white balance module and generating auto white balance data. The method further includes detecting a backlight condition based on the auto white balance data. An apparatus to automatically detect a backlight condition is also disclosed.

Abstract: In a particular embodiment, a method is disclosed that includes determining at least one ambient exposure parameter using an ambient illumination, the at least one ambient exposure parameter including a first sensitivity parameter of an autoexposure controller using the ambient illumination. The method includes determining at least one low-illumination parameter using a first lamp level, the at least one low-illumination parameter including a second sensitivity parameter of the autoexposure controller using the first lamp level, where the autoexposure controller is configured to operate according to at least one high-illumination parameter based on the at least one ambient exposure parameter and the at least one low-illumination parameter. The method further includes performing an image capture operation using a second lamp level that is brighter than the first lamp level, where the at least one high-illumination parameter includes a third sensitivity parameter.

Abstract: In a particular embodiment, a method is disclosed that includes comparing a frame rate of image capture by an image sensor to a frame rate threshold at an image capture device. The method also includes when the frame rate is less than the frame rate threshold, increasing the frame rate to a modified frame rate that is greater than or at least equal to the frame rate threshold. The method further includes performing an autofocus operation on an image to be captured at the modified frame rate.

Abstract: In a particular embodiment, a method is disclosed that includes performing a first test using a first pixel value of a pixel to determine whether the pixel is outside a skin color region of a color space. The method includes, when the first test does not identify the pixel as outside the skin color region, performing a second test using a second pixel value of the pixel to determine whether the pixel is outside the skin color region of the color space. The method further includes, when the second test does not identify the pixel as outside the skin color region, performing a third test using a third pixel value of the pixel to determine whether the pixel is outside the skin color region of the color space.

Abstract: Image processing methods and systems are disclosed. In a particular embodiment, a method is disclosed that includes receiving image data. The image data includes color component data representing a location of a pixel in a color space. The method further includes performing a linear transformation of the location of the pixel in the color space when the location is identified as within a skin color region of the color space. The linear transformation is performed by mapping the location of the pixel at a first portion of the skin color region to a second portion of the skin color region based on a position of the pixel within the skin color region and based on the proximity of the position of the pixel to a boundary of the skin color region. The color space remains substantially continuous at the boundary of the skin color region after applying the linear transformation.