我首先通过opencv读取一张
image = cv2.imread(filepath)
再用网上贴的RGB转HSI得到这张图片的hue、saturation和intensity，再分别输出他们
def RGB2HSI(rgb_img):
"""
这是将RGB彩色图像转化为HSI图像的函数
:param rgm_img: RGB彩色图像
:return: HSI图像
"""
#保存原始图像的行列数
row = np.shape(rgb_img)[0]
col = np.shape(rgb_img)[1]
#对原始图像进行复制
hsi_img = rgb_img.copy()
#对图像进行通道拆分
B,G,R = cv2.split(rgb_img)
#把通道归一化到[0,1]
[B,G,R] = [ i/ 255.0 for i in ([B,G,R])]
H = np.zeros((row, col)) #定义H通道
I = (R + G + B) / 3.0 #计算I通道
S = np.zeros((row,col)) #定义S通道
for i in range(row):
den = np.sqrt((R[i]-G[i])**2+(R[i]-B[i])*(G[i]-B[i]))
thetha = np.arccos(0.5*(R[i]-B[i]+R[i]-G[i])/den) #计算夹角
h = np.zeros(col) #定义临时数组
#den>0且G>=B的元素h赋值为thetha
h[B[i]<=G[i]] = thetha[B[i]<=G[i]]
#den>0且G<=B的元素h赋值为thetha
h[G[i]<B[i]] = 2*np.pi-thetha[G[i]<B[i]]
#den<0的元素h赋值为0
h[den == 0] = 0
H[i] = h/(2*np.pi) #弧度化后赋值给H通道
#计算S通道
for i in range(row):
min = []
#找出每组RGB值的最小值
for j in range(col):
arr = [B[i][j],G[i][j],R[i][j]]
min.append(np.min(arr))
min = np.array(min)
#计算S通道
S[i] = 1 - min*3/(R[i]+B[i]+G[i])
#I为0的值直接赋值0
S[i][R[i]+B[i]+G[i] == 0] = 0
#扩充到255以方便显示，一般H分量在[0,2pi]之间，S和I在[0,1]之间
hsi_img[:,:,0] = H*255
hsi_img[:,:,1] = S*255
hsi_img[:,:,2] = I*255
return hsi_img
再把它们合并后，再转回RGB
original = cv2.merge((hue, saturation, intensity))
original = HSI2RGB(original)
def HSI2RGB(hsi_img):
"""
这是将HSI图像转化为RGB图像的函数
:param hsi_img: HSI彩色图像
:return: RGB图像
"""
# 保存原始图像的行列数
row = np.shape(hsi_img)[0]
col = np.shape(hsi_img)[1]
#对原始图像进行复制
rgb_img = hsi_img.copy()
#对图像进行通道拆分
H,S,I = cv2.split(hsi_img)
#把通道归一化到[0,1]
[H,S,I] = [ i/ 255.0 for i in ([H,S,I])]
R,G,B = H,S,I
for i in range(row):
h = H[i]*2*np.pi
#H大于等于0小于120度时
a1 = h >=0
a2 = h < 2*np.pi/3
a = a1 & a2 #第一种情况的花式索引
tmp = np.cos(np.pi / 3 - h)
b = I[i] * (1 - S[i])
r = I[i]*(1+S[i]*np.cos(h)/tmp)
g = 3*I[i]-r-b
B[i][a] = b[a]
R[i][a] = r[a]
G[i][a] = g[a]
#H大于等于120度小于240度
a1 = h >= 2*np.pi/3
a2 = h < 4*np.pi/3
a = a1 & a2 #第二种情况的花式索引
tmp = np.cos(np.pi - h)
r = I[i] * (1 - S[i])
g = I[i]*(1+S[i]*np.cos(h-2*np.pi/3)/tmp)
b = 3 * I[i] - r - g
R[i][a] = r[a]
G[i][a] = g[a]
B[i][a] = b[a]
#H大于等于240度小于360度
a1 = h >= 4 * np.pi / 3
a2 = h < 2 * np.pi
a = a1 & a2 #第三种情况的花式索引
tmp = np.cos(5 * np.pi / 3 - h)
g = I[i] * (1-S[i])
b = I[i]*(1+S[i]*np.cos(h-4*np.pi/3)/tmp)
r = 3 * I[i] - g - b
B[i][a] = b[a]
G[i][a] = g[a]
R[i][a] = r[a]
rgb_img[:,:,0] = B*255
rgb_img[:,:,1] = G*255
rgb_img[:,:,2] = R*255
return rgb_img
得到图片
为什么这张图与原图不一样呢？我没有做过任何的操作啊？
求大佬指点！！！
