Method and system for generating output image data

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.

1 . (canceled) 
     
     
         2 . A method comprising:
 applying a first function to a reference image;   obtaining a first result of applying the first function to the reference image;   applying a second function to an output image data;   obtaining a second result of applying the second function to the output image data;   computing a difference between the first result and the second result;   obtaining a third result by applying a third function to the difference between the first result and the second result, and a constant that is proportional to the magnitude of the output image data;   generating a constraint for the output image data based on the third result; and   updating the output image data based on the first result and the constraint.   
     
     
         3 . The method of  claim 2 , wherein applying the first function to the reference image comprises applying a derivate function to the reference image. 
     
     
         4 . The method of  claim 3 , wherein the first result includes derivative data corresponding to the reference image. 
     
     
         5 . The method of  claim 4 , wherein the derivative data corresponding to the reference image comprises a fourth function of a derivative of reference image data, and wherein the reference image data comprises a fifth function of the reference image that is distinct from the fourth function. 
     
     
         6 . The method of  claim 5 , wherein the fourth function is one of a threshold function, an attenuating function and a clip function. 
     
     
         7 . The method of  claim 5 , further comprising:
 setting the mean of the output image data to equal the mean of the reference image data.   
     
     
         8 . The method of  claim 5 , wherein the fifth function includes a homomorphic function, and wherein the homomorphic function includes a logarithm function. 
     
     
         9 . The method of  claim 5 , further comprising:
 applying the inverse of the fifth function to the output image data to generate an output image.   
     
     
         10 . The method of  claim 2 , wherein applying the second function to the output image data comprises applying a derivate function to the output image data. 
     
     
         11 . The method of  claim 10 , wherein the second result includes derivative data corresponding to the output image data. 
     
     
         12 . The method of  claim 2 , wherein the third function includes a sum that is applied to the difference between the first result and the second result, and a penalty term that is a product of the constant and a magnitude of the output image data. 
     
     
         13 . The method of  claim 12 , further comprising:
 minimizing the sum based on an algorithm that is selected from the group consisting of the Gauss-Seidel method and the Jacobi method.   
     
     
         14 . The method of  claim 13 , wherein the first result and the penalty term are selected such that minimizing the sum can be achieved by a convolution function. 
     
     
         15 . The method of  claim 2 , wherein the constant is inversely proportional to the magnitude of the output image data. 
     
     
         16 . The method of  claim 2 , wherein the constraint comprises that the output image be a linear combination of a set of smooth functions that are based on the first M terms of a discrete cosine basis. 
     
     
         17 . A non-transitory computer-readable medium storing instructions, that, when executed by a processor, are configured to cause the processor to perform operations comprising:
 applying a first function to a reference image;   obtaining a first result of applying the first function to the reference image;   applying a second function to an output image data;   obtaining a second result of applying the second function to the output image data;   computing a difference between the first result and the second result;   obtaining a third result by applying a third function to the difference between the first result and the second result, and a constant that is proportional to the magnitude of the output image data;   generating a constraint for the output image data based on the third result; and   updating the output image data based on the first result and the constraint.   
     
     
         18 . The non-transitory computer-readable medium of  claim 17 , wherein applying the first function to the reference image comprises applying a derivate function to the reference image. 
     
     
         19 . The non-transitory computer-readable medium of  claim 18 , wherein the first result includes derivative data corresponding to the reference image. 
     
     
         20 . The non-transitory computer-readable medium of  claim 17 , wherein applying the second function to the output image data comprises applying a derivate function to the output image data. 
     
     
         21 . The non-transitory computer-readable medium of  claim 20 , wherein the second result includes derivative data corresponding to the output image data. 
     
     
         22 . The non-transitory computer-readable medium of  claim 17 , wherein the third function includes a sum that is applied to the difference between the first result and the second result, and a penalty term that is a product of the constant and a magnitude of the output image data. 
     
     
         23 . The non-transitory computer-readable medium of  claim 17 , wherein the constant is inversely proportional to the magnitude of the output image data.