H-maxima transform
H-maxima transform can be explained as a way to find peaks in a picture, just like when you are looking for the highest point on a mountain. In this case, the picture is divided into different regions, with each region containing different pixels.
Imagine each pixel in the picture as a small square box, and the height of each box is determined by the brightness of the color in that pixel. If the color is bright, the box will be tall, and if the color is dim, the box will be short.
Now, the h-maxima transform comes into play. It involves picking a particular value 'h' and comparing the height of each box in the picture with this value 'h'. If any box's height is less than or equal to 'h', it is marked as insignificant and the color value is set to zero. This step helps to clean out any noise in the image that might interfere with identifying the peaks.
Once this cleaning is done, the picture is analyzed again, but this time, the height of every box is compared with its neighboring boxes, and the highest box in each group is chosen as the representative of that group.
Finally, the resulting picture will have regions that have been identified as peaks since those regions will contain the highest boxes after the comparison. H-maxima transform is useful in cases where you want to highlight the peaks in an image, and it can be applied in many fields such as medical imaging, remote sensing, and more.
Imagine each pixel in the picture as a small square box, and the height of each box is determined by the brightness of the color in that pixel. If the color is bright, the box will be tall, and if the color is dim, the box will be short.
Now, the h-maxima transform comes into play. It involves picking a particular value 'h' and comparing the height of each box in the picture with this value 'h'. If any box's height is less than or equal to 'h', it is marked as insignificant and the color value is set to zero. This step helps to clean out any noise in the image that might interfere with identifying the peaks.
Once this cleaning is done, the picture is analyzed again, but this time, the height of every box is compared with its neighboring boxes, and the highest box in each group is chosen as the representative of that group.
Finally, the resulting picture will have regions that have been identified as peaks since those regions will contain the highest boxes after the comparison. H-maxima transform is useful in cases where you want to highlight the peaks in an image, and it can be applied in many fields such as medical imaging, remote sensing, and more.