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Task-Specific Information: An Imaging System Analysis Amit Ashoka, Pawan K. Bahetia and Mark A. Neifelda, b
 

Summary: Task-Specific Information: An Imaging System Analysis
Tool
Amit Ashoka, Pawan K. Bahetia and Mark A. Neifelda, b
aDepartment of Electrical and Computer Engineering, 1230 East Speedway Blvd,
University of Arizona, Tucson, AZ 85721, USA;
bCollege of Optical Sciences, 1630 East University Boulevard, University of Arizona,
Tucson, AZ 85721, USA
ABSTRACT
We present a novel method for computing the information content of an image. We introduce the notion
of task-specific information (TSI) in order to quantify imaging system performance for a given task. This
new approach employs a recently-discovered relationship between the Shannon mutual-information and
minimum estimation error. We demonstrate the utility of the TSI formulation by applying it to several
familiar imaging systems including (a) geometric imagers, (b) diffraction-limiter imagers, and (c) projec-
tive/compressive imagers. Imaging system TSI performance is analyzed for two tasks: (a) detection, and
(b) classification.
Keywords: Entropy, Mutual Information, Minimum-mean square error, Diffraction-limited imager
1. INTRODUCTION
Information content of an image is an important measure that finds applications ranging from evaluating
compression algorithm performance to designing imaging systems.15
However, the computation of image

  

Source: Ashok, Amit - Department of Electrical and Computer Engineering, University of Arizona

 

Collections: Engineering