Information transfer function for image compression algorithms

Paul G. Cox; Ronald G. Driggers

doi:10.1117/12.276084

16 June 1997 Information transfer function for image compression algorithms

Paul G. Cox, Ronald G. Driggers

Proceedings Volume 3063, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing VIII; (1997) https://doi.org/10.1117/12.276084
Event: AeroSense '97, 1997, Orlando, FL, United States

Abstract

Electro-optical and infrared systems are usually approximated to be Linear Shift Invariant (LSI) systems and are characterized by Modulation Transfer Functions (MTF). Each component in these systems has an MTF that describes the modulation throughput as a function of spatial frequency. Image compression is becoming a component in these systems, but unfortunately, cannot be described by the typical MTF. Image compression output signals can be very different than input signals in not only modulation, but frequency and phase. Therefore, the compression system is neither linear or shift invariant. We proposed an Information Transfer Function (ITF) that can be used in a manner similar to the MTF. This ITF describes the correlation between the input image and the output image as a function of spatial frequency, compression ratio, and image complexity. Like MTF, ITF can be used to determine image compression requirements to maintain system spatial resolution.

Citation Download Citation

Paul G. Cox and Ronald G. Driggers "Information transfer function for image compression algorithms", Proc. SPIE 3063, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing VIII, (16 June 1997); https://doi.org/10.1117/12.276084

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