### Ex 2.3

Verfasst:

**13. Jun 2013 21:49**Hi,

I have a question concering the task description. It is said that we should apply non-maximum suppression. The task describes non-maximum suppression as the extraction of the local maximum in a 5x5 neighborhood. So all pixels, aside from the maximum, are cancled out (set to zero). I don't understand the neighborhood itself. Is it a 5x5 window which is shifted over the harris values (withoud overlapping, e.g. first position 1, next postion 6). Or do we lay the neighborhood window over each pixel (if yes, there would be a lot of interest points left, also after thresholding; or are already determined local maximas are earesed if they are in a grid of a neighbor pixel which contains a larger value).

Moreover, I have a question concerning image coordinates and filters. Regarding central differences, we may have the following filter 0.5 [-1 0 1]. This filter is defined in the direction of the image's x axis. So, I though it is the x filter for correlation (since correlation is applied by overlaying the filter and multiplying the pixels with the weight and summing them up). But I got some how confused and I am not sure if its the x-axis filter for correlation or connvolution. Also the slides provide no way to differ between convolution an correlation filters. So I just wanted to ask, how I can differ between both (are correlation or convolution x-axis filters are defined in the x direction of the image).

I have a question concering the task description. It is said that we should apply non-maximum suppression. The task describes non-maximum suppression as the extraction of the local maximum in a 5x5 neighborhood. So all pixels, aside from the maximum, are cancled out (set to zero). I don't understand the neighborhood itself. Is it a 5x5 window which is shifted over the harris values (withoud overlapping, e.g. first position 1, next postion 6). Or do we lay the neighborhood window over each pixel (if yes, there would be a lot of interest points left, also after thresholding; or are already determined local maximas are earesed if they are in a grid of a neighbor pixel which contains a larger value).

Moreover, I have a question concerning image coordinates and filters. Regarding central differences, we may have the following filter 0.5 [-1 0 1]. This filter is defined in the direction of the image's x axis. So, I though it is the x filter for correlation (since correlation is applied by overlaying the filter and multiplying the pixels with the weight and summing them up). But I got some how confused and I am not sure if its the x-axis filter for correlation or connvolution. Also the slides provide no way to differ between convolution an correlation filters. So I just wanted to ask, how I can differ between both (are correlation or convolution x-axis filters are defined in the x direction of the image).