暗通道去雾代码,Python代码库,德仔网

代码语言
代码分类
【Python】暗通道去雾
作者:暗通道去雾 liaoqb / 发布于2015/2/15/ 818

	#!/usr/bin/env python
	# -*- coding: utf-8 -*-
	
	from PIL import Image
	from guidedfilter import *
	
	def getDark(input_img, filter, frame):
	 """get dark image from the input image"""
	 size = input_img.size
	 output = []
	
	 for x in xrange(size[1]):
	 temp = []
	 for y in xrange(size[0]):
	 temp.append(min(input_img.getpixel((y, x))))
	
	 output.append(temp)
	
	 output = filter2d(output, filter, frame)
	
	 output_img = Image.new('L', size)
	
	 for x in xrange(size[1]):
	 for y in xrange(size[0]):
	 output_img.putpixel((y, x), output[x][y])
	
	 return output_img
	
	def getLight(srcImage, darkImage, cut):
	 """get atmospheric light from the picture"""
	 size = darkImage.size
	 light = []
	
	 for x in xrange(size[0]):
	 for y in xrange(size[1]):
	 light.append(darkImage.getpixel((x, y)))
	
	 light.sort()
	 light.reverse()
	
	 threshold = light[int(cut * len(light))]
	
	 atmosphere = {}
	
	 for x in xrange(size[0]):
	 for y in xrange(size[1]):
	 if darkImage.getpixel((x, y)) >= threshold:
	 atmosphere.update({(x, y): sum(srcImage.getpixel((x, y))) / 3.0})
	
	 pos = sorted(atmosphere.iteritems(), key = lambda item: item[1], reverse = True)[0][0]
	
	 return srcImage.getpixel(pos)
	
	def getTransmission(input_img, light, omiga):
	 """get transmission from the picture"""
	 size = input_img.size
	 output = []
	
	 for x in xrange(size[1]):
	 temp = []
	 for y in xrange(size[0]):
	 temp.append(min(input_img.getpixel((y, x))) / float(min(light)))
	
	 output.append(temp)
	
	 transmission = []
	
	 for x in xrange(size[1]):
	 temp = []
	 for y in xrange(size[0]):
	 temp.append(1 - omiga * minimizeFilter(output, (x, y), (10, 10)))
	
	 transmission.append(temp)
	
	 return transmission
	
	def getRadiance(input_img, transmission, light, t0):
	 """get radiance from the picture"""
	 size = input_img.size
	 output = Image.new('RGB', size)
	
	 for x in xrange(size[1]):
	 for y in xrange(size[0]):
	 r, g, b = input_img.getpixel((y, x))
	
	 r = int((r - light[0]) / float(max(t0, transmission[x][y])) + light[0])
	 g = int((g - light[1]) / float(max(t0, transmission[x][y])) + light[1])
	 b = int((b - light[2]) / float(max(t0, transmission[x][y])) + light[2])
	
	 output.putpixel((y, x), (r, g, b))
	
	 return output
	
	def ensure(n):
	 if n < 0:
	 n = 0
	
	 if n > 255:
	 n = 255
	
	 return int(n)
	
	if __name__ == '__main__':
	 image = Image.open('yellowmountain.jpg')
	 image = image.convert('RGB')
	
	 dark = getDark(image, minimizeFilter, (10, 10))
	
	 dark.save('yellowmountain_dark.png')
	
	 light = getLight(image, dark, 0.001)
	
	 transmission = getTransmission(image, light, 0.9)
	
	 tranImage = Image.new('L', image.size)
	 grayImage = image.convert('L')
	
	 for x in xrange(image.size[0]):
	 for y in xrange(image.size[1]):
	 tranImage.putpixel((x, y), int(transmission[y][x] * 255))
	
	 guided = guidedFilter(grayImage, tranImage, 25, 0.001)
	
	 guidedImage = Image.new('L', image.size)
	
	 for x in xrange(image.size[0]):
	 for y in xrange(image.size[1]):
	 guidedImage.putpixel((x, y), ensure(guided[y][x]))
	 guided[y][x] /= 255.0
	
	 #guidedImage.show()
	 guidedImage.save('yellowmountain_guided.png')
	
	 output = getRadiance(image, guided, light, 0.1)
	
	 output.save('yellowmountain_guide_haze.png')
	4. [文件] guidedfilter.py ~ 4KB 下载(1)
	?
	1
	2
	3
	4
	5
	6
	7
	8
	9
	10
	11
	12
	13
	14
	15
	16
	17
	18
	19
	20
	21
	22
	23
	24
	25
	26
	27
	28
	29
	30
	31
	32
	33
	34
	35
	36
	37
	38
	39
	40
	41
	42
	43
	44
	45
	46
	47
	48
	49
	50
	51
	52
	53
	54
	55
	56
	57
	58
	59
	60
	61
	62
	63
	64
	65
	66
	67
	68
	69
	70
	71
	72
	73
	74
	75
	76
	77
	78
	79
	80
	81
	82
	83
	84
	85
	86
	87
	88
	89
	90
	91
	92
	93
	94
	95
	96
	97
	98
	99
	100
	101
	102
	103
	104
	105
	106
	107
	108
	109
	110
	111
	112
	113
	114
	115
	116
	117
	118
	119
	120
	121
	122
	123
	124
	125
	126
	127
	128
	129
	130
	131
	132
	133
	134
	135
	136
	137
	138
	139
	140
	141
	142
	143
	144
	145
	146
	147
	148
	149
	150
	151
	152
	153
	154
	155
	156
	157
	158
	#!/usr/bin/env python
	# -*- coding: utf-8 -*-
	
	from PIL import Image
	
	def filter2d(input_img, filter, frame):
	 """filter of the 2-dimension picture"""
	 size = len(input_img), len(input_img[0])
	 output = []
	
	 for i in xrange(size[0]):
	 temp = []
	 for j in xrange(size[1]):
	 temp.append(filter(input_img, (i, j), frame))
	
	 output.append(temp)
	
	 return output
	
	def minimizeFilter(input_img, point, size):
	 """minimize filter for the input image"""
	 begin = (point[0] - size[0] / 2, point[0] + size[0] / 2 + 1)
	 end = (point[1] - size[1] / 2, point[1] + size[1] / 2 + 1)
	
	 l = []
	
	 for i in xrange(*begin):
	 for j in xrange(*end):
	 if (i >= 0 and i < len(input_img)) and (j >= 0 and j < len(input_img[0])):
	 l.append(input_img[i][j])
	
	 return min(l)
	
	def convertImageToMatrix(image):
	 size = image.size
	 out = []
	
	 for x in xrange(size[1]):
	 temp = []
	 for y in xrange(size[0]):
	 temp.append(image.getpixel((y, x)))
	
	 out.append(temp)
	
	 return out
	
	def boxFilter(im, radius):
	 """box filter for the image of the radius"""
	 height, width = len(im), len(im[0])
	
	 imDst = []
	 imCum = []
	
	 for x in xrange(height):
	 imDst.append([0.0] * width)
	 imCum.append([0.0] * width)
	
	 #cumulative sum over Y axis
	 for i in xrange(width):
	 for j in xrange(height):
	 if j == 0:
	 imCum[j][i] = im[j][i]
	 else:
	 imCum[j][i] = im[j][i] + imCum[j - 1][i]
	
	 #difference over Y axis
	 for j in xrange(radius + 1):
	 for i in xrange(width):
	 imDst[j][i] = imCum[j + radius][i]
	
	 for j in xrange(radius + 1, height - radius):
	 for i in xrange(width):
	 imDst[j][i] = imCum[j + radius][i] - imCum[j - radius - 1][i]
	
	 for j in xrange(height - radius, height):
	 for i in xrange(width):
	 imDst[j][i] = imCum[height - 1][i] - imCum[j - radius - 1][i]
	
	 #cumulative sum over X axis
	 for j in xrange(height):
	 for i in xrange(width):
	 if i == 0:
	 imCum[j][i] = imDst[j][i]
	 else:
	 imCum[j][i] = imDst[j][i] + imCum[j][i - 1]
	
	 #difference over X axis
	 for j in xrange(height):
	 for i in xrange(radius + 1):
	 imDst[j][i] = imCum[j][i + radius]
	
	 for j in xrange(height):
	 for i in xrange(radius + 1, width - radius):
	 imDst[j][i] = imCum[j][i + radius] - imCum[j][i - radius - 1]
	
	 for j in xrange(height):
	 for i in xrange(width - radius, width):
	 imDst[j][i] = imCum[j][width - 1] - imCum[j][i - radius - 1]
	
	 return imDst
	
	def dot(matrix1, matrix2, operation):
	 """dot operation for the matrix1 and matrix2"""
	 out = []
	 size = len(matrix1), len(matrix1[0])
	
	 for x in xrange(size[0]):
	 temp = []
	 for y in xrange(size[1]):
	 temp.append(operation(matrix1[x][y], matrix2[x][y]))
	
	 out.append(temp)
	
	 return out
	
	def guidedFilter(srcImage, guidedImage, radius, epsilon):
	 """guided filter for the image
	 src image must be gray image
	 guided image must be gray image
	 """
	
	 size = srcImage.size
	 src = convertImageToMatrix(srcImage)
	 guided = convertImageToMatrix(guidedImage)
	
	 one = []
	
	 for x in xrange(size[1]):
	 one.append([1.0] * size[0])
	
	 n = boxFilter(one, radius)
	
	 plus = lambda x, y: x + y
	 minus = lambda x, y: x - y
	 multiple = lambda x, y: x * y
	 divide = lambda x, y: x / y
	
	 meanI = dot(boxFilter(src, radius), n, divide)
	 meanP = dot(boxFilter(guided, radius), n, divide)
	 meanIP = dot(boxFilter(dot(src, guided, multiple), radius), n, divide)
	
	 covIP = dot(meanIP, dot(meanI, meanP, multiple), minus)
	
	 meanII = dot(boxFilter(dot(src, src, multiple), radius), n, divide)
	 varI = dot(meanII, dot(meanI, meanI, multiple), minus)
	
	 epsilonMatrix = []
	
	 for x in xrange(size[1]):
	 epsilonMatrix.append([epsilon] * size[0])
	
	 a = dot(covIP, dot(varI, epsilonMatrix, plus), divide)
	 b = dot(meanP, dot(a, meanI, multiple), minus)
	
	 meanA = dot(boxFilter(a, radius), n, divide)
	 meanB = dot(boxFilter(b, radius), n, divide)
	
	 return dot(dot(meanA, src, multiple), meanB, plus)
评论列表
本站所提供的代码，版权归原作者所有，若有侵犯作者版权，请与我们联系，我们将立即删除或修改。谢谢!
本站所有代码发布及提供者。
试试其它关键字
　暗通道去雾　
同语言下
可能有用的
暗通道去雾 liaoqb贡献的其它代码(1)
.暗通道去雾