I am trying to teach myself about the WHT but there dont seem to be many good explanations of it online anywhere. I think I have figured out how to calculate the WHT, but I am really trying to understand why it is considered useful within the image recognition domain.
What is so special about it, and what properties does it bring out in a signal that would not show up on classical Fourier transforms, or other wavelet transforms? Why is it useful for object recognition as pointed out here?
Answer
NASA used to use the Hadamard transform as a basis for compressing photographs from interplanetary probes during the 1960's and early '70s. Hadamard is a computationally simpler substitute for the Fourier transform, since it requires no multiplication or division operations (all factors are plus or minus one). Multiply and divide operations were extremely time intensive on the small computers used on board those spacecraft, so avoiding them was beneficial both in terms of compute time and energy consumption. But since the development of faster computers incorporating single-cycle multipliers, and perfection of newer algorithms such as the Fast Fourier Transform, as well as the development of JPEG, MPEG, and other image compression, I believe Hadamard has fallen out of use. However, I understand it may be staging a comeback for use in quantum computing. (NASA use is from an old article in NASA Tech Briefs; exact attribution unavailable.)
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