大津の手法を用いた二値化

max.compute

// Each #kernel tells which function to compile; you can have many kernels
#pragma kernel CSMain

// Create a RenderTexture with enableRandomWrite flag and set it
// with cs.SetTexture
RWStructuredBuffer<float2> data;

[numthreads(8,8,1)]
void CSMain (uint3 id : SV_DispatchThreadID)
{
	float2 w = float2(1, 0);
	w = lerp(data[id.x*2], data[id.x*2+1], step(data[id.x*2].y, data[id.x*2+1].y));

	AllMemoryBarrierWithGroupSync();
	data[id.x] = w;
}

Otsu.compute

// Each #kernel tells which function to compile; you can have many kernels
#pragma kernel CSMain

// Create a RenderTexture with enableRandomWrite flag and set it
// with cs.SetTexture

StructuredBuffer<int> histogram;
RWStructuredBuffer<float2> result; //x:thresh, y:variable

float num1, num2;  //画素数
float sum1, sum2;  //和
float m1, m2;      //平均

[numthreads(8,8,1)]
void CSMain (uint3 id : SV_DispatchThreadID)
{
	float w = 0;
	uint i=0;
	num1=0;
	num2=0;
	sum1=0;
	sum2=0;
	m1=0;
	m2=0;

	for(i=0; i<id.x; i++){
		num1 += histogram[i];
		sum1 += histogram[i]*i;
	}
	m1 = sum1/num1;

	for(i=id.x; i<256; i++){
		num2 += histogram[i];
		sum2 += histogram[i]*i;
	}
	m2 = sum2/num2;

	w = num1 * num2 * (m1 - m2) * (m1 - m2);

	if(isfinite(w)){
		result[id.x] = float2( (float)id.x, w);
	}
	else{
		result[id.x] = float2((float)id.x, 0);
	}
	
}