Question

我试图通过首先将RGB颜色空间转换为HSI颜色空间，在强度通道上进行直方图均衡，然后转换回RGB颜色空间来实现图像增强。

然而，输出图像看起来不太好，我无法弄清楚原因。请帮帮我。

我的RGB HSI转换方法基于以下网站：https://hypjudy.github.io/2017/03/19/dip-histogram-equalization/

我的输入图片：enter image description here 我的输出图片：enter image description here

import cv2
from math import acos
from math import cos
from math import sqrt
from math import pi


# Read the bmp file
img = cv2.imread('/Users/xxx/xxx/input3.bmp')
# Read the width and height of the image
shape = img.shape

# HSI array to store original histogram
H_origin_hist = [[0 for i in range(0, shape[1])] for j in range(0, shape[0])] 
S_origin_hist = [[0 for i in range(0, shape[1])] for j in range(0, shape[0])] 
I_origin_hist = [0] * 256
I_hist = [0] * 256

# Convert colors from RGB to HSI and calculate histogram
for i in range(0, shape[0]) :
    for j in range(0, shape[1]) :
        # px[0], px[1], and px[2] represents B, G, and R respectively
        px = img[i,j]
        R = int(px[2])
        G = int(px[1])
        B = int(px[0])
        # Calculate HSI original histogram
        numerator = float(0.5 * ((R - G) + (R - B)))
        denominator = float(sqrt((R - G) * (R - G) + (R - B) * (G - B)))
        if (denominator == 0) :
            val = 0.0
        else :
            val = numerator / denominator
        theta = acos(val)
        I = (B + G + R) / 3
        if (B <= G) :
            H_origin_hist[i][j]= theta
        else :
            H_origin_hist[i][j] = 2 * pi - theta
        if(R == 0 or G == 0 or B == 0) :
            S_origin_hist[i][j] = 0
            H_origin_hist[i][j] = 0
        else :
            S_origin_hist[i][j] = 1 - (3.0 / (R + G + B) * min(R, G, B))
        I_origin_hist[I] = I_origin_hist[I] + 1


# Do histogram equalization on the intensity channel
for i in range(0, 256) :
    I_hist[i] = ((sum(I_origin_hist[0:i+1]) - min(I_origin_hist)) * 255) / (shape[0] * shape[1])

# Convert colors from HSI to RGB
for i in range(0, shape[0]) :
    for j in range(0, shape[1]) :
        px = img[i,j]
        R = int(px[2])
        G = int(px[1])
        B = int(px[0])
        I = (R + G + B) / 3
        if (H_origin_hist[i][j] >= 0 and H_origin_hist[i][j] < 2 * pi / 3) :
            H = H_origin_hist[i][j]
            h = ((pi / 3) - H_origin_hist[i][j])
            px[0] = (1 - S_origin_hist[i][j]) * I_hist[I]
            px[2] = (1 + (S_origin_hist[i][j] * cos(H) / cos(h))) * I_hist[I]
            px[1] = 1 - B - R
        elif (H_origin_hist[i][j] >= 2 * pi / 3 and H_origin_hist[i][j] < 4 * pi / 3) :
            H = (H_origin_hist[i][j] - (2 * pi / 3))
            h = (pi - H_origin_hist[i][j])
            px[2] = (1 - S_origin_hist[i][j]) * I_hist[I]
            px[1] = (1 + (S_origin_hist[i][j] * cos(H) / cos(h))) * I_hist[I]
            px[0] = 1 - G - R
        else :
            H = (H_origin_hist[i][j] - (4 * pi / 3))
            h = ((5 * pi / 6) - H_origin_hist[i][j])
            px[1] = (1 - S_origin_hist[i][j]) * I_hist[I]
            px[0] = (1 + (S_origin_hist[i][j] * cos(H) / cos(h))) * I_hist[I]
            px[2] = 1 - B - G

# Write back to bmp file
cv2.imwrite('/Users/xxx/xxx/output3.bmp', img)

图像增强（RGB HSI转换）

0 个答案: