Could someone explain what this filter would do? I'm a little confused by what exactly it does or why it is a good pre-filter in the context of Nyquist sampling.
litony396
@oligonagon As shown in slide 57 in this lecture, a kernel like this would act like a low-pass filter, which only lets low frequency signals come out. It is a good pre-filter because the low frequency output after putting the image through the filter will be under the Nyquist frequency. But, I'm not sure why exactly a 1-pixel width filter would be the best choice, hopefully someone else can answer that.
Boomaa23
This might be a simple question, but what is a box filter? I see that the image in the spatial domain is a box which presumably is one pixel wide, but is that the filter? If so, would a 1px box filter on a 1px box image just return the same original 1px? I guess what I'm asking is what does a box filter do if it's only 1px; every pixel of an image is 1px which is the smallest subdivision possible.
Could someone explain what this filter would do? I'm a little confused by what exactly it does or why it is a good pre-filter in the context of Nyquist sampling.
@oligonagon As shown in slide 57 in this lecture, a kernel like this would act like a low-pass filter, which only lets low frequency signals come out. It is a good pre-filter because the low frequency output after putting the image through the filter will be under the Nyquist frequency. But, I'm not sure why exactly a 1-pixel width filter would be the best choice, hopefully someone else can answer that.
This might be a simple question, but what is a box filter? I see that the image in the spatial domain is a box which presumably is one pixel wide, but is that the filter? If so, would a 1px box filter on a 1px box image just return the same original 1px? I guess what I'm asking is what does a box filter do if it's only 1px; every pixel of an image is 1px which is the smallest subdivision possible.