Abstract
Correlation using binary images is suited to efficient digital realization or convenient optical implementation. Binarization algorithms are required in order to match grayscale imagery to these binary corre- lation architectures. We present several novel point-wise and block-wise binarization techniques all of which outperform the grayscale matched filter for large values of input signal-to-noise ratio (SNR50 dB). We dis- cuss direct binarization methods based on global thresholds, local thresholds, histogram equalization, edge-enhancement, and statistical binarization, as well as indirect methods based on auto- and cross- correlation techniques. These point-wise methods are shown to offer poor noise tolerance and a new block-wise binarization method is intro- duced to enhance recognition at low values of SNR. This block-wise technique is motivated by vector quantization-based image compression and offers performance superior to the grayscale matched filter for an input SNR as low as 212 dB. © 1999 Society of Photo-Optical Instrumentation Engineers. (S0091-3286(99)02611-2)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
