照片的RGB转称HSI

学习目标：

RGB颜色空间转换成HSI

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学习代码：

def rgbtohsi(rgb_lwpImg):
    rows = int(rgb_lwpImg.shape[0])
    cols = int(rgb_lwpImg.shape[1])
    b, g, r = cv2.split(rgb_lwpImg)
    # 归一化到[0,1]
    b = b / 255.0
    g = g / 255.0
    r = r / 255.0
    hsi_lwpImg = rgb_lwpImg.copy()
    H,S,I = cv2.split(hsi_lwpImg)
    for i in range(rows):
        for j in range(cols):
            num = 0.5 * ((r[i,j]-g[i,j])+(r[i,j]-b[i,j]))
            den = np.sqrt((r[i,j]-g[i,j])**2+(r[i,j]-b[i,j])*(g[i,j]-b[i,j]))
            theta = float(np.arccos(num/den))
            if den == 0:
                    H = 0
            elif b[i,j] <= g[i,j]:
                H = theta
            else:
                H = 2*3.14169265 - theta
            min_RGB = min(min(b[i,j],g[i,j]),r[i,j])
            sum = b[i,j]+g[i,j]+r[i,j]
            if sum == 0:
                S = 0
            else:
                S = 1 - 3*min_RGB/sum
            H = H/(2*3.14159265)
            I = sum/3.0
            # 输出HSI图像，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_lwpImg[i,j,0] = H*255
            hsi_lwpImg[i,j,1] = S*255
            hsi_lwpImg[i,j,2] = I*255
    return hsi_lwpImg

rgb_lwpImg = cv2.imread("body.jpg")
hsi_lwpImg = rgbtohsi(rgb_lwpImg)
cv2.imshow('rgb_lwpImg',rgb_lwpImg)
cv2.imshow('hsi_lwpImg',hsi_lwpImg)
key = cv2.waitKey(0) & 0xFF
if key == ord('q'):
    cv2.destroyAllWindows()