Apple Inc.

University of East Anglia

Other

Mark Drew

Graham D Finlayson

Clement Fredembach

David Connah

Cheng Lu

Devices, methods, and non-transitory program storage devices are disclosed herein to provide improved image processing, the techniques comprising: obtaining an input image and target image data, and then calculating derivatives for the target image data using a regularized derivative kernel operator. In some embodiments, the regularized operator may comprise the following operator: [&#x2212;1 (1+&#x3b5;)], wherein &#x3b5; may be a controllable system parameter and preferably is independent of the particular type of image processing being applied to the image. In some embodiments, the techniques may find look-up table (LUT) mappings or analytical functions to approximate the derivative structure of the target image data. Finally, the techniques disclosed herein may generate an output image from the input image based on attempting to closely approximate the calculated derivatives for the target image data. In preferred embodiments, by controlling the mapping, e.g., using regularization techniques, halos and other image artifacts may be ameliorated.

Regularized derivative operators for image processing system and method

A method and system for producing a scalar image from a derivative field and a vector image is disclosed. A function class c is selected, where all members of the class c are functions which map each vector of the vector image to a unique scalar value. A function f is selected from the class c which maps the vector image to a scalar image, the derivative of which is closest to the derivative field. The scalar image is generated from the vector image by using f to calculate each scalar value in the scalar image from a corresponding vector in the vector image.

Image reconstruction method and system

A method and system for producing accented image data for an accented image is disclosed. The method includes decomposing each of a first and a second image into a gradient representation which comprises spectral and edge components. The first image comprises more spectral dimensions than the second image. The edge component from the first image is combined with the spectral component from the second image to form a combined gradient representation. Accented image data for the accented image is then generated from data including the combined gradient representation.

Method and system for generating accented image data

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.

Detecting illumination in images

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.

In a method for the recovery of an invariant image from a 3-band colour image, information relating to the angle for an 'invariant direction' in a log-chromaticity space is obtained on the basis that the correction projection is that which minimizes entropy in the resulting invariant image. The method is applied to remove shadows from unsourced imagery.

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Vancouver, Canada

Mark Drew