Method and Apparatus for Compressive Imaging Device

Abstract

A new digital image/video camera that directly acquires random projections of the incident light field without first collecting the pixels/voxels. In one preferred embodiment, the camera employs a digital micromirror array to perform optical calculations of linear projections of an image onto pseudorandom binary patterns. Its hallmarks include the ability to obtain an image with only a single detection element while measuring the image/video fewer times than the number of pixels or voxels—this can significantly reduce the computation required for image/video acquisition/encoding. Since the system features a single photon detector, it can also be adapted to image at wavelengths that are currently impossible with conventional CCD and CMOS imagers.

1 . A method for acquiring an image or video sequence from incoherent projections comprising the steps of: 
 modulating an incident light field by a series of patterns;    optically computing inner products between the light field and said series of patterns; and    reconstructing an image or video sequence based upon said inner products.    
   
   
       2 . A method for acquiring an image or video sequence from incoherent projections according to  claim 1  wherein said image or video sequence is reconstructed with fewer inner products than a number of pixels or voxels reconstructed.  
   
   
       3 . A method for acquiring an image or video sequence according to  claim 1 , wherein said step of optically computing inner products comprises integrating the modulated light field at a number of points.  
   
   
       4 . A method for acquiring an image or video sequence according to  claim 1 , wherein said step of optically computing inner products comprises transmitting light through some material.  
   
   
       5 . A method for acquiring an image or video sequence according to  claim 1 , wherein said step of optically computing inner products comprises reflecting light off an array of reflective surfaces, where each surface corresponds to an area of said image being integrated.  
   
   
       6 . A method for acquiring an image or video sequence according to  claim 1 , wherein said step of optically computing inner products comprises reflecting light off a contoured surface.  
   
   
       7 . A method for acquiring an image or video sequence according to  claim 1 , further comprising the steps of: 
 taking additional measurements; and    using said additional measurements for subsequent processing.    
   
   
       8 . A method for acquiring an image or video sequence according to  claim 7 , wherein said subsequent processing comprises filtering, averaging or other processing.  
   
   
       9 . An imaging system comprising: 
 means for modulating an incident light field by a series of patterns;    means for optically computing inner products between the light field and a series of patterns; and    means for recovering a signal based upon said inner products.    
   
   
       10 . An imaging system according to  claim 9 , wherein said means for modulating comprises at least one of a digital micromirror device array, an LCD shutter array, and a physically moving shutter array.  
   
   
       11 . An imaging system according to  claim 9 , wherein said means for modulating comprises a material that can be made more or less transparent to a light field of interest at different points in space.  
   
   
       12 . An imaging system according to  claim 9 , wherein said means for recovering a signal comprises: 
 a single sensing element; and    a processor for applying a reconstruction algorithm to signals received from said single sensing element.    
   
   
       13 . An imaging system according to  claim 12 , wherein said single sensing element comprises a photodiode.  
   
   
       14 . An imaging system according to  claim 9 , wherein said means for recovering a signal recovers a signal using fewer measurements than a number of pixels or voxels to be recovered.  
   
   
       15 . An imaging system according to  claim 9 , wherein said means for recovering a signal comprises: 
 a plurality of sensing elements; and    a processor for applying a reconstruction algorithm to signals received from said plurality of sensing elements.    
   
   
       16 . An imaging system according to  claim 15 , wherein said plurality of sensing elements comprise a number of photodetectors.  
   
   
       17 . An imaging system according to  claim 15 , wherein said plurality of sensing elements comprise a number of stacked photodetectors.  
   
   
       18 . An imaging device comprising: 
 a lens;    a digital micromirror device array;    means for modulating mirror orientations of said digital micromirror device array in an incoherent pattern sequence;    a pattern generator for supplying incoherent patterns to said means for modulating;    a sensor element, wherein each different mirror pattern produces a voltage at the sensor element that corresponds to a measurement;    an analog-to-digital converter for quantizing said voltage; and    a reconstruction means for reconstructing an image based upon a bitstream received from said analog-to-digital converter.    
   
   
       19 . An imaging device according to  claim 18 , wherein said image is a color, multispectral or hyperspectral image or a color, multispectral or hyperspectral video sequence.  
   
   
       20 . An imaging device according to  claim 18 , wherein said reconstruction means comprises a processor for performing a reconstruction algorithm.  
   
   
       21 . An imaging device according to  claim 20 , wherein said reconstruction algorithm comprises at least one of a Greedy reconstruction algorithm, Matching Pursuit, Orthogonal Matching Pursuit, Basis Pursuit, group testing, LASSO, LARS, expectation-maximization, Bayesian estimation algorithm, belief propagation, wavelet-structure exploiting algorithm, Sudocode reconstruction, reconstruction based on manifolds, l 1  reconstruction, l 0  reconstruction, and l 2  reconstruction.  
   
   
       22 . An imaging device according to  claim 18 , where said lens comprises a biconvex lens.  
   
   
       23 . An imaging device according to  claim 18 , further comprising a second lens for focusing an image onto said sensing element.  
   
   
       24 . An imaging device according to  claim 18 , wherein said means for modulating comprises measurement matrices having most adjacent rows similar to one another.  
   
   
       25 . An imaging device according to  claim 18 , wherein said means for modulating comprises at least one of discrete valued measurement matrices, real valued measurement matrices, randomly distributed matrices with real values, randomly distributed matrices with discrete values, random Bernoulli-distributed matrices, random Gaussian-distributed matrices, permutation matrices, modulation matrices, structured binary matrices, sparse matrices, Sudocode matrices, code matrices, parity check matrices, and matrices having adjacent rows designed to minimize the power required to transition from one pattern to the next.  
   
   
       26 . An imaging device comprising: 
 a sensing element; and    means for focusing light onto said sensing element for measurement;    wherein measurements taken by said sensing element correspond to inner products of an incident image with a sequence of incoherent patterns.    
   
   
       27 . A method of acquiring a signal comprising the steps of: 
 measuring and encoding projections of a signal that is compressible in a first set of basis functions onto a second set of basis functions, wherein said second set of basis functions is incoherent with said first set of basis functions;    reconstructing said signal based upon said projections.    
   
   
       28 . A method for acquiring a signal according to  claim 27  wherein said signal is a signal of two or more dimensions  
   
   
       29 . A method for acquiring a signal according to  claim 27  wherein said reconstructing step is based on at least one of a Greedy reconstruction algorithm, Matching Pursuit, Orthogonal Matching Pursuit, Basis Pursuit, group testing, LASSO, LARS, expectation-maximization, Bayesian estimation algorithm, belief propagation, wavelet-structure exploiting algorithm, Sudocode reconstruction, reconstruction based on manifolds, l 1  reconstruction, l 0  reconstruction, and l 2  reconstruction.