Commit a88ba837 authored by Nathaniel Callens's avatar Nathaniel Callens
Browse files

histogram experiments

parent 2aa38181

compress_start.py

+12 −8
Original line number Original line Diff line number Diff line
@@ -101,18 +101,18 @@ def plot_hist(tiff_list): 
    image = Image.open(image)    #Open the image and read it as an Image object

    image = Image.open(image)    #Open the image and read it as an Image object

    image = np.array(image)[1:,:]    #Convert to an array, leaving out the first row because the first row is just housekeeping data

    image = np.array(image)[1:,:]    #Convert to an array, leaving out the first row because the first row is just housekeeping data

    row, col = image.shape

    row, col = image.shape

    predict = np.empty(row,col)     # create a empty matrix to update prediction

    predict = np.empty((row,col))     # create a empty matrix to update prediction

    predict[0,:] = image[0,:]       # keep the first row from the image

    predict[0,:] = image[0,:]       # keep the first row from the image

    predict[:,0] = image[:,0]       # keep the first columen from the image

    predict[:,0] = image[:,0]       # keep the first columen from the image

    diff = np.empty(row,col)

    diff = np.empty((row,col))

    diff[0,:] = np.zeros(row)       # keep the first row from the image

    diff[0,:] = np.zeros(col)       # keep the first row from the image

    diff[:,0] = np.zeros(col)

    diff[:,0] = np.zeros(row)

    for r in range(1,row):                  # loop through the rth row

    for r in range(1,row-1):                  # loop through the rth row

        for c in range(1,col):              # loop through the cth column

        for c in range(1,col-1):              # loop through the cth column

            surrounding = anp.array([predict[r-1,c-1], predict[r-1,c], predict[r-1,c+1], predict[r1,c-1]])

            surrounding = np.array([predict[r-1,c-1], predict[r-1,c], predict[r-1,c+1], predict[r,c-1]])

            predict[r,c] = np.mean(surrounding)       # take the mean of the previous 4 pixels

            predict[r,c] = np.mean(surrounding)       # take the mean of the previous 4 pixels

            diff[r,c] = (np.max(surrounding)-np.min(surrounding))

            diff[r,c] = (np.max(surrounding)-np.min(surrounding))

    

    return image, predict, diff





if __name__ == '__main__':

if __name__ == '__main__':
@@ -124,5 +124,9 @@ if __name__ == '__main__': 
    

    

    scenes = file_extractor()

    scenes = file_extractor()

    images = image_extractor(scenes)

    images = image_extractor(scenes)

    image, predict, difference = plot_hist(images)

    error = np.abs(image-predict)

    

    

    

    

    
    
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