Abstract: Embodiments disclosed herein are directed to devices and methods for performing spatially-varying brightness correction of a flash image. The spatially-varying brightness correction utilizes a set of images that includes one or more images captured under flash illumination and one or more images captured without flash illumination, which are used to decompose one of the flash images or an image generated therefrom into a flash contribution image and an ambient contribution image. The flash contribution image and the ambient contribution image are recombined to generate a corrected flash image, and information about the flash module and/or scene is used to adjust the relative contributions of these images during recombination.

Abstract: Techniques to generate global tone-mapping operators (G-TMOs) that, when applied to high dynamic range images, visually approximate the use of spatially varying tone-mapping operators (SV-TMOs) are described. The disclosed G-TMOs provide substantially the same visual benefits as SV-TMOs but do not suffer from spatial artifacts such as halos and are, in addition, computationally efficient compared to SV-TMOs. In general, G-TMOs may be identified based on application of a SV-TMO to a down-sampled version of a full-resolution input image (e.g., a thumbnail). An optimized mapping between the SV-TMO's input and output constitutes the G-TMO. It has been unexpectedly discovered that when optimized (e.g., to minimize the error between the SV-TMO's input and output), G-TMOs so generated provide an excellent visual approximation to the SV-TMO (as applied to the full-resolution image).

Abstract: Techniques to generate global tone-mapping operators (G-TMOs) that, when applied to high dynamic range images, visually approximate the use of spatially varying tone-mapping operators (SV-TMOs) are described. The disclosed G-TMOs provide substantially the same visual benefits as SV-TMOs but do not suffer from spatial artifacts such as halos and are, in addition, computationally efficient compared to SV-TMOs. In general, G-TMOs may be identified based on application of a SV-TMO to a down-sampled version of a full-resolution input image (e.g., a thumbnail). An optimized mapping between the SV-TMO's input and output constitutes the G-TMO. It has been unexpectedly discovered that when optimized (e.g., to minimize the error between the SV-TMO's input and output), G-TMOs so generated provide an excellent visual approximation to the SV-TMO (as applied to the full-resolution image).

Abstract: Techniques to generate global tone-mapping operators (G-TMOs) that, when applied to high dynamic range images, visually approximate the use of spatially varying tone-mapping operators (SV-TMOs) are described. The disclosed G-TMOs provide substantially the same visual benefits as SV-TMOs but do not suffer from spatial artifacts such as halos and are, in addition, computationally efficient compared to SV-TMOs. In general, G-TMOs may be identified based on application of a SV-TMO to a down-sampled version of a full-resolution input image (e.g., a thumbnail). An optimized mapping between the SV-TMO's input and output constitutes the G-TMO. It has been unexpectedly discovered that when optimized (e.g., to minimize the error between the SV-TMO's input and output), G-TMOs so generated provide an excellent visual approximation to the SV-TMO (as applied to the full-resolution image).

Abstract: Techniques to generate global tone-mapping operators (G-TMOs) that, when applied to high dynamic range images, visually approximate the use of spatially varying tone-mapping operators (SV-TMOs) are described. The disclosed G-TMOs provide substantially the same visual benefits as SV-TMOs but do not suffer from spatial artifacts such as halos and are, in addition, computationally efficient compared to SV-TMOs. In general, G-TMOs may be identified based on application of a SV-TMO to a down-sampled version of a full-resolution input image (e.g., a thumbnail). An optimized mapping between the SV-TMO's input and output constitutes the G-TMO. It has been unexpectedly discovered that when optimized (e.g., to minimize the error between the SV-TMO's input and output), G-TMOs so generated provide an excellent visual approximation to the SV-TMO (as applied to the full-resolution image).

Abstract: A method of generating an image enhancement function for enhancing an input image comprising a plurality of pixels to form an enhanced output image. The method includes receiving a reference image comprising a plurality of pixels; receiving an enhanced image derived from the reference image comprising a corresponding plurality of pixels; calculating a plurality of lookup tables, each of which maps a first plurality of pixel values to a second plurality of pixel values; and generating the image enhancement function comprising a spatially varying function of the lookup tables which when applied to the reference image generates an approximation to the enhanced image.

Abstract: Techniques to generate global tone-mapping operators (G-TMOs) that, when applied to high dynamic range images, visually approximate the use of spatially varying tone-mapping operators (SV-TMOs) are described. The disclosed G-TMOs provide substantially the same visual benefits as SV-TMOs but do not suffer from spatial artifacts such as halos and are, in addition, computationally efficient compared to SV-TMOs. In general, G-TMOs may be identified based on application of a SV-TMO to a down-sampled version of a full-resolution input image (e.g., a thumbnail). An optimized mapping between the SV-TMO's input and output constitutes the G-TMO. It has been unexpectedly discovered that when optimized (e.g., to minimize the error between the SV-TMO's input and output), G-TMOs so generated provide an excellent visual approximation to the SV-TMO (as applied to the full-resolution image).

Abstract: A method of generating output image data comprises obtaining derivative data relating to a reference image; obtaining a constraint for output image data; and generating the output image data from the derivative data relating to the reference image in dependence on the constraint. This method can be used to recover a robust output image from the derivative of an input image.

Abstract: Systems, methods, and computer readable media to approximate edge-preserving transformations with global transfer functions are described. In general, a first transfer function that approximates an edge-preserving operation can be found which, together with an enhancement filter (e.g., dynamic range compression) may be used to generate a global transfer function. Alternatively, a second transfer function may be found that approximates the behavior of the combined first transfer function and enhancement filter. Together the first and second transfer functions may generate a global transfer function. It has been determined that a down-sampled version of an input image may be used to develop the global transfer function. Application of global transfer functions in accordance with this disclosure can generate an output image that exhibits the same overall tonality of the input image without introducing the loss of detail and other artifacts attributable to local processing (e.g.

Abstract: Systems and techniques can be used to correct color of an image by expanding red, green, blue (RGB) values at each pixel of the image using a base of order-root functions f(R,G,B). In one aspect, a method includes receiving an image, where a plurality of pixels of the received image have input RGB values that depend on a sensor used to acquire the image; expanding, by an image processor, the input RGB values of the plurality of pixels using a nonlinear base, such that each term of the nonlinear base scales linearly with exposure or brightness of the image; and adjusting, by the image processor, the image by transforming the expanded input RGB values of the image to output RGB values that are independent of the sensor used to acquire the image and scale linearly with the exposure or illumination of the image.

Abstract: A method of generating output image data comprises obtaining derivative data relating to a reference image; obtaining a constraint for output image data; and generating the output image data from the derivative data relating to the reference image in dependence on the constraint. This method can be used to recover a robust output image from the derivative of an input image.

Abstract: In a method of chromagenic illuminant estimation pixels from mutually-corresponding images with different filtering are compared, a fraction of the brightest pixels being selected for a subsequent chromagenic estimation. The pixels may be at corresponding locations or they may correspond in that their mean brightness is in the same rank order. In one method, in which, in a first preprocessing stage, for a database of m lights Ei(?) and n surfaces Sj(?) there is calculated Ti˜QFQ+ where Q1F and QF represent the matrices of unfiltered and filtered sensor responses to the n surfaces under the i th light and + denotes an inverse, and in a second operation stage, given P surfaces in an image and 3×P matrices Q and QF, from these matrices there are chosen the r % brightest pixels giving the matrices Q? and Q?F, and the scene illuminant Pest is estimated where formula (I) and (II).

Abstract: Systems, methods, and computer readable media to approximate edge-preserving transformations with global transfer functions are described. In general, a first transfer function that approximates an edge-preserving operation can be found which, together with an enhancement filter (e.g., dynamic range compression) may be used to generate a global transfer function. Alternatively, a second transfer function may be found that approximates the behavior of the combined first transfer function and enhancement filter. Together the first and second transfer functions may generate a global transfer function. It has been determined that a down-sampled version of an input image may be used to develop the global transfer function. Application of global transfer functions in accordance with this disclosure can generate an output image that exhibits the same overall tonality of the input image without introducing the loss of detail and other artifacts attributable to local processing (e.g.

Abstract: Techniques to generate global tone-mapping operators (G-TMOs) that, when applied to high dynamic range images, visually approximate the use of spatially varying tone-mapping operators (SV-TMOs) are described. The disclosed G-TMOs provide substantially the same visual benefits as SV-TMOs but do not suffer from spatial artifacts such as halos and are, in addition, computationally efficient compared to SV-TMOs. In general, G-TMOs may be identified based on application of a SV-TMO to a down-sampled version of a full-resolution input image (e.g., a thumbnail). An optimized mapping between the SV-TMO's input and output constitutes the G-TMO. It has been unexpectedly discovered that when optimized (e.g., to minimize the error between the SV-TMO's input and output), G-TMOs so generated provide an excellent visual approximation to the SV-TMO (as applied to the full-resolution image).

Abstract: Systems and techniques can be used to correct color of an image by expanding red, green, blue (RGB) values at each pixel of the image using a base of order-root functions f(R, G, B). In one aspect, a method includes receiving an image, where a plurality of pixels of the received image have input RGB values that depend on a sensor used to acquire the image; expanding, by an image processor, the input RGB values of the plurality of pixels using a nonlinear base, such that each term of the nonlinear base scales linearly with exposure or brightness of the image; and adjusting, by the image processor, the image by transforming the expanded input RGB values of the image to output RGB values that are independent of the sensor used to acquire the image and scale linearly with the exposure or illumination of the image.

Abstract: An image having m light sources, with m preferably equaling 2 or 3, is segmented into different regions, each of which is lit by only one of the m light sources, by obtaining paired imaged with different filtering, for example a filtered and an unfiltered image, applying to the image pairs sets of m pre-computed mappings at the pixel or region level, and selecting the most appropriate. The rendering of the information in the image maybe adjusted accordingly.

Abstract: A method of generating output image data comprises obtaining derivative data relating to a reference image; obtaining a constraint for output image data; and generating the output image data from the derivative data relating to the reference image in dependence on the constraint. This method can be used to recover a robust output image from the derivative of an input image.

Abstract: A method of generating an image enhancement function for enhancing an input image comprising a plurality of pixels to form an enhanced output image. The method includes receiving a reference image comprising a plurality of pixels; receiving an enhanced image derived from the reference image comprising a corresponding plurality of pixels; calculating a plurality of lookup tables, each of which maps a first plurality of pixel values to a second plurality of pixel values; and generating the image enhancement function comprising a spatially varying function of the lookup tables which when applied to the reference image generates an approximation to the enhanced image.

Abstract: In a method of chromagenic illuminant estimation pixels from mutually-corresponding images with different filtering (e.g. a filtered image and an unfiltered image) are compared, a fraction of the brightest pixels being selected for a subsequent chromagenic estimation. The pixels may be at corresponding locations or they may correspond in that their mean brightness is in the same rank order. In one method, in which, in a first preprocessing stage, for a database of m lights Ei (?) and n surfaces Sj (?) there is calculated Ti˜QF Q+ where Q1F and QF represent the matrices of unfiltered and filtered sensor responses to the n surfaces under the i th light and + denotes an inverse, and in a second operation stage, given P surfaces in an image and 3×P matrices Q and QF, from these matrices there are chosen the r % brightest pixels giving the matrices Q? and Q?F, and the scene illuminant Pest is estimated where formula (I) and (II).

Abstract: An image having m light sources, with m preferably equaling 2 or 3, is sequenced into different regions, each of which is lit by only one of the m light sources, by obtaining paired imaged with different filtering, for example a filtered and an unfiltered image, applying to the image pairs sets of m pre-computed mappings at the pixel or region level, and selecting the most appropriate. The rendering of the information in the image maybe adjusted accordingly.