Dear researchers,
i am working on disparity estimation methods. I am using sum of squared difference methods.The method is applied on two images with different views.I got the disparity map. I got a disparity map with zeros ,ones and two's.My asumption is that region covered with 0's in map shows similarity and other regions with 1's and 2 shows dissimilarity.This is my assumption.I would like to measure the similarity in the map in terms of number of 1's covering the regions.
My point is that my methodology is correct or not? please advice me in this regard?
Dear Venkata,
Your question is too vague to be able to assemble a meaningful answer. Please provide more details on your problem and in particular address the following points:
- What is the origin of your stereo images (ground-based, airborne or space-borne) and what is their spatial resolution?
- What is the nature of your target, and is it flat or rough (i.e., if it is a land surface, does it include topography)?
- Have these images been co-registered so that pixel (i, j) in both images correspond to the same point on the target?
- What are the format and mathematical nature of your stereo images (Black and White, RGB or multi-spectral; binary, integer, floating point)?
- What method did you use to generate the 0/1/2 values included in your 'similarity.xlsx' file? Specifically, the sum of squared differences between the values retrieved from two images would yield a single number, so I don't understand how you could map that...
- Also, what is the intended meaning of the scores 0, 1, and 2?
Once your problem and your approach are better understood, it may be possible to provide some guidance about how to proceed. Cheers, Michel.
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