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Parametrize quantization error decay and minimum value. The latter

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helps with images where there are large solid colour fields that
sometimes cause uneven dithering because of colours that cannot be
matched with the //gs palette, but it's not a viable solution in
general since it reduces overall quality (sometimes substantially,
e.g. in case of vertical colour gradients)
This commit is contained in:
kris 2021-11-25 09:09:40 +00:00
parent 8b5c3dc6c1
commit 870c008827
1 changed files with 18 additions and 14 deletions
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32
dither.pyx
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@ -355,6 +355,9 @@ def dither_shr(
cdef double[::1] palette_line_errors = np.zeros(200, dtype=np.float64)
cdef PaletteSelection palette_line
cdef float decay = 0.5
cdef float min_quant_error = 0.0 # 0.02
best_palette = -1
total_image_error = 0.0
for y in range(200):
@ -387,6 +390,8 @@ def dither_shr(
for i in range(3):
quant_error = working_image[y, x, i] - best_colour_rgb[i]
if abs(quant_error) <= min_quant_error:
quant_error = 0
# Floyd-Steinberg dither
# 0 * 7
@ -396,15 +401,14 @@ def dither_shr(
working_image[y, x + 1, i] = clip(
working_image[y, x + 1, i] + quant_error * (7 / 16), 0, 1)
if y < 199:
# TODO: parametrize the 0.5x decay factor
if x > 0:
working_image[y + 1, x - 1, i] = clip(
working_image[y + 1, x - 1, i] + quant_error * (3 / 32), 0, 1)
working_image[y + 1, x - 1, i] + decay * quant_error * (3 / 32), 0, 1)
working_image[y + 1, x, i] = clip(
working_image[y + 1, x, i] + quant_error * (5 / 32), 0, 1)
working_image[y + 1, x, i] + decay * quant_error * (5 / 32), 0, 1)
if x < 319:
working_image[y + 1, x + 1, i] = clip(
working_image[y + 1, x + 1, i] + quant_error * (1 / 32), 0, 1)
working_image[y + 1, x + 1, i] + decay * quant_error * (1 / 32), 0, 1)
# # 0 0 X 7 5
# # 3 5 7 5 3
@ -418,40 +422,40 @@ def dither_shr(
#if y < 199:
# if x > 1:
# working_image[y + 1, x - 2, i] = clip(
# working_image[y + 1, x - 2, i] + quant_error * (3 / 48), 0,
# working_image[y + 1, x - 2, i] + decay * quant_error * (3 / 48), 0,
# 1)
# if x > 0:
# working_image[y + 1, x - 1, i] = clip(
# working_image[y + 1, x - 1, i] + quant_error * (5 / 48), 0,
# working_image[y + 1, x - 1, i] + decay * quant_error * (5 / 48), 0,
# 1)
# working_image[y + 1, x, i] = clip(
# working_image[y + 1, x, i] + quant_error * (7 / 48), 0, 1)
# working_image[y + 1, x, i] + decay * quant_error * (7 / 48), 0, 1)
# if x < 319:
# working_image[y + 1, x + 1, i] = clip(
# working_image[y + 1, x + 1, i] + quant_error * (5 / 48),
# working_image[y + 1, x + 1, i] + decay * quant_error * (5 / 48),
# 0, 1)
# if x < 318:
# working_image[y + 1, x + 2, i] = clip(
# working_image[y + 1, x + 2, i] + quant_error * (3 / 48),
# working_image[y + 1, x + 2, i] + decay * quant_error * (3 / 48),
# 0, 1)
#if y < 198:
# if x > 1:
# working_image[y + 2, x - 2, i] = clip(
# working_image[y + 2, x - 2, i] + quant_error * (1 / 48), 0,
# working_image[y + 2, x - 2, i] + decay * decay * quant_error * (1 / 48), 0,
# 1)
# if x > 0:
# working_image[y + 2, x - 1, i] = clip(
# working_image[y + 2, x - 1, i] + quant_error * (3 / 48), 0,
# working_image[y + 2, x - 1, i] + decay * decay * quant_error * (3 / 48), 0,
# 1)
# working_image[y + 2, x, i] = clip(
# working_image[y + 2, x, i] + quant_error * (5 / 48), 0, 1)
# working_image[y + 2, x, i] + decay * decay * quant_error * (5 / 48), 0, 1)
# if x < 319:
# working_image[y + 2, x + 1, i] = clip(
# working_image[y + 2, x + 1, i] + quant_error * (3 / 48),
# working_image[y + 2, x + 1, i] + decay * decay * quant_error * (3 / 48),
# 0, 1)
# if x < 318:
# working_image[y + 2, x + 2, i] = clip(
# working_image[y + 2, x + 2, i] + quant_error * (1 / 48),
# working_image[y + 2, x + 2, i] + decay * decay * quant_error * (1 / 48),
# 0, 1)
return np.array(output_4bit, dtype=np.uint8), line_to_palette, total_image_error, np.array(palette_line_errors, dtype=np.float64)