TrIQ

trim the head intensity data by a given cutoff threshold which is evaluated via the TrIQ algorithm.

The Threshold Intensity Quantization addresses this issue by setting a new upper limit T

the upper bound raw value of the threshold

get the best value range for level scaler via TrIQ algorithm.

[min,max] of the data range.

Quantization is a process for mapping a range of analog intensity values To a Single discrete value, known As a gray level.

Quantization is a process For mapping a range of analog intensity values To a Single discrete value, known As a gray level. Zero-memory Is a widely used quantization method. The zero-memory quantizer computes equally spaced intensity bins Of width w:

 w = (max(f) - min(f)) / n

where n represents the number Of discrete values, usually 256; min(f) And max(f) operators provide minimum And maximum intensity values. Quantization Is based On a comparison with the transition levels tk:

 tk = w + min(f), 2w + min(f), ..., nw + min(f)

Finally, the discrete mapped value Q Is obtained:

 Q(f(x, y)) = {
     
     0,  f(x,y) <= t1
     k,  tk < f(x,y) < tk+1
 }