Merge branch 'master' of https://git.elphel.com/nathaniel/image-compression

    diff = []

    diff = []

    for ii in range(len(tiff1)):

    for ii in range(len(tiff1)):

        image = Image.open(tiff1[ii])

        image = Image.open(tiff1[ii])    #Open the image and read it as an Image object

        image = np.array(image)[1:,:]

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

        ar1, ar2 = image.shape

        ar1, ar2 = image.shape

        ind1, ind2 = np.random.randint(0,ar1), np.random.randint(0,ar2)

        ind1, ind2 = np.random.randint(0,ar1), np.random.randint(0,ar2) #ind1 randomly selects a row, ind2 randomly selects a column, 

        surrounding = []

                                                                        #this is now a random pixel selection within the image

        for i,j in product(np.arange(-1,2), repeat=2):

            if i == 0 and j == 0:

        surrounding = []                                                #initialize a list to be filled the 8 surrounding pixels

        for i,j in product(np.arange(-1,2), repeat=2):                  #Iterate through the combinations of surrounding pixel indices

            if i == 0 and j == 0:                                       #Avoid the target pixel

                continue

                continue

            else:

            else:

                surrounding.append(image[ind1+i, ind1+j])

                surrounding.append(image[ind1+i, ind1+j])               #Add the other 8 pixels to the list

        diff.append(np.max(surrounding)-np.min(surrounding))

        diff.append(np.max(surrounding)-np.min(surrounding))