deleted 6 characters in body

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edited Jan 11, 2019 at 4:51

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I am extracting the sharpness features of image as shown in the following image mentioned in a paper.

I have done with the following code. Firstly, use the open cv convert the RGB to HSL (luminance is L mentioned in the paper), then get L array. and then used the Laplacian operator to get the LP. Finally, obtain the sharpness value of image based on mathematical form in the paper.

img_HLS = cv2.cvtColor(image, cv2.COLOR_BGR2HLS)
L = img_HLS[:, :, 1]
u = np.mean(L)
LP = cv2.Laplacian(L, cv2.CV_16S, ksize = 3)  
s = np.sum(gray_lapLP/u)

I don't know my solution is right or wrong, if there is problem, please help me correct it. Thank!

I am extracting the sharpness features of image as shown in the following image mentioned in a paper.

I have done with the following code. Firstly, use the open cv convert the RGB to HSL (luminance is L mentioned in the paper), then get L array. and then used the Laplacian operator to get the LP. Finally, obtain the sharpness value of image based on mathematical form in the paper.

img_HLS = cv2.cvtColor(image, cv2.COLOR_BGR2HLS)
L = img_HLS[:, :, 1]
u = np.mean(L)
LP = cv2.Laplacian(L, cv2.CV_16S, ksize = 3)  
s = np.sum(gray_lap/u)

I don't know my solution is right or wrong, if there is problem, please help me correct it. Thank!

I am extracting the sharpness features of image as shown in the following image mentioned in a paper.

I have done with the following code. Firstly, use the open cv convert the RGB to HSL (luminance is L mentioned in the paper), then get L array. and then used the Laplacian operator to get the LP. Finally, obtain the sharpness value of image based on mathematical form in the paper.

img_HLS = cv2.cvtColor(image, cv2.COLOR_BGR2HLS)
L = img_HLS[:, :, 1]
u = np.mean(L)
LP = cv2.Laplacian(L, cv2.CV_16S, ksize = 3)  
s = np.sum(LP/u)

I don't know my solution is right or wrong, if there is problem, please help me correct it. Thank!

Formatting code better.

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edited Jan 9, 2019 at 20:37

Peter K. ♦

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I am extracting the sharpness features of image as shown in the following image mentioned in a paper.

I have done with the following code. Firstly, use the open cv convert the RGB to HSL (luminance is L mentioned in the paper), then get L array. and then used the Laplacian operator to get the LP. Finally, obtain the sharpness value of image based on mathematical form in the paper.

     img_HLS = cv2.cvtColor(image, cv2.COLOR_BGR2HLS)
     L = img_HLS[:, :, 1]
     u = np.mean(L)
    LP = cv2.Laplacian(L, cv2.CV_16S, ksize = 3)  
    s = np.sum(gray_lap/u)

I don't know my solution is right or wrong, if there is problem, please help me correct it. Thank!

I am extracting the sharpness features of image as shown in the following image mentioned in a paper.

I have done with the following code. Firstly, use the open cv convert the RGB to HSL (luminance is L mentioned in the paper), then get L array. and then used the Laplacian operator to get the LP. Finally, obtain the sharpness value of image based on mathematical form in the paper.

     img_HLS = cv2.cvtColor(image, cv2.COLOR_BGR2HLS)
     L = img_HLS[:, :, 1]
     u = np.mean(L)
    LP = cv2.Laplacian(L, cv2.CV_16S, ksize = 3)  
    s = np.sum(gray_lap/u)

I don't know my solution is right or wrong, if there is problem, please help me correct it. Thank!

I am extracting the sharpness features of image as shown in the following image mentioned in a paper.

I have done with the following code. Firstly, use the open cv convert the RGB to HSL (luminance is L mentioned in the paper), then get L array. and then used the Laplacian operator to get the LP. Finally, obtain the sharpness value of image based on mathematical form in the paper.

img_HLS = cv2.cvtColor(image, cv2.COLOR_BGR2HLS)
L = img_HLS[:, :, 1]
u = np.mean(L)
LP = cv2.Laplacian(L, cv2.CV_16S, ksize = 3)  
s = np.sum(gray_lap/u)

I don't know my solution is right or wrong, if there is problem, please help me correct it. Thank!

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asked Jan 9, 2019 at 6:16

tktktk0711

103
1
6

python: how to compute the sharpness features of image

I am extracting the sharpness features of image as shown in the following image mentioned in a paper.

I have done with the following code. Firstly, use the open cv convert the RGB to HSL (luminance is L mentioned in the paper), then get L array. and then used the Laplacian operator to get the LP. Finally, obtain the sharpness value of image based on mathematical form in the paper.

     img_HLS = cv2.cvtColor(image, cv2.COLOR_BGR2HLS)
     L = img_HLS[:, :, 1]
     u = np.mean(L)
    LP = cv2.Laplacian(L, cv2.CV_16S, ksize = 3)  
    s = np.sum(gray_lap/u)

I don't know my solution is right or wrong, if there is problem, please help me correct it. Thank!

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python: how to compute the sharpness features of image