Open DLFCW opened 5 years ago
@DLFCW My cpu is 3.9Ghz, the run time of constant median filter with radius 5 and image size 1280x1024 is about 140 ms.
And the HISTOGRAM_LEN
should be 256 not 512, https://github.com/Ldpe2G/ArmNeonOptimization/blob/master/ConstantTimeMedianFilter/src/constant_time_median_filter_uint16.h#L8
After you change it to 256, you should see a little speed up.
And by the way, if your image size is too large and filter radius is small, it is not recommended to use this algorithm, because you need to allocate a large chunck of memory to store the column histograms.
You can simply try to use the parallel strategy like the normal median filter dose:
https://github.com/Ldpe2G/ArmNeonOptimization/blob/master/ConstantTimeMedianFilter/src/normal_median_filter_uint16.cpp#L27
@DLFCW My cpu is 3.9Ghz, the run time of constant median filter with radius 5 and image size 1280x1024 is about 140 ms. And the
HISTOGRAM_LEN
should be 256 not 512, https://github.com/Ldpe2G/ArmNeonOptimization/blob/master/ConstantTimeMedianFilter/src/constant_time_median_filter_uint16.h#L8 After you change it to 256, you should see a little speed up. And by the way, if your image size is too large and filter radius is small, it is not recommended to use this algorithm, because you need to allocate a large chunck of memory to store the column histograms. You can simply try to use the parallel strategy like the normal median filter dose: https://github.com/Ldpe2G/ArmNeonOptimization/blob/master/ConstantTimeMedianFilter/src/normal_median_filter_uint16.cpp#L27
do you know halcon? a machine vision library . The library run constant median filter only 0.9ms in same condition
No, have not heard before, the library must be done a lot optimization. I have just implemented the basic algorithm described in the paper, and there are some optimization tips described in the paper that I did not try.
Radius 5 In 3.4Ghz Cpu i use avx2 to improve add histogram and sub histogram but the time speed greater than 200ms image size 1280*1024