颜色空间变换（RGB-HSV）

#!/usr/bin/env python
#******************************************************************************
#  $Id$
# 
#  Project:  GDAL Python Interface
#  Purpose:  Script to merge greyscale as intensity into an RGB(A) image, for
#            instance to apply hillshading to a dem colour relief.
#  Author:   Frank Warmerdam, [email protected]
#            Trent Hare (USGS)
# 
#******************************************************************************
#  Copyright (c) 2009, Frank Warmerdam
#  Copyright (c) 2010, Even Rouault 
# 
#  Permission is hereby granted, free of charge, to any person obtaining a
#  copy of this software and associated documentation files (the "Software"),
#  to deal in the Software without restriction, including without limitation
#  the rights to use, copy, modify, merge, publish, distribute, sublicense,
#  and/or sell copies of the Software, and to permit persons to whom the
#  Software is furnished to do so, subject to the following conditions:
# 
#  The above copyright notice and this permission notice shall be included
#  in all copies or substantial portions of the Software.
# 
#  THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
#  OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
#  FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
#  THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
#  LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
#  FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
#  DEALINGS IN THE SOFTWARE.
#******************************************************************************

from osgeo import gdal
import numpy
import sys

# =============================================================================
# rgb_to_hsv()
#
# rgb comes in as [r,g,b] with values in the range [0,255].  The returned
# hsv values will be with hue and saturation in the range [0,1] and value
# in the range [0,255]
#
def rgb_to_hsv( r,g,b ):

    maxc = numpy.maximum(r,numpy.maximum(g,b))
    minc = numpy.minimum(r,numpy.minimum(g,b))

    v = maxc

    minc_eq_maxc = numpy.equal(minc,maxc)

    # compute the difference, but reset zeros to ones to avoid divide by zeros later.
    ones = numpy.ones((r.shape[0],r.shape[1]))
    maxc_minus_minc = numpy.choose( minc_eq_maxc, (maxc-minc,ones) )

    s = (maxc-minc) / numpy.maximum(ones,maxc)
    rc = (maxc-r) / maxc_minus_minc
    gc = (maxc-g) / maxc_minus_minc
    bc = (maxc-b) / maxc_minus_minc

    maxc_is_r = numpy.equal(maxc,r)
    maxc_is_g = numpy.equal(maxc,g)
    maxc_is_b = numpy.equal(maxc,b)

    h = numpy.zeros((r.shape[0],r.shape[1]))
    h = numpy.choose( maxc_is_b, (h,4.0+gc-rc) )
    h = numpy.choose( maxc_is_g, (h,2.0+rc-bc) )
    h = numpy.choose( maxc_is_r, (h,bc-gc) )

    h = numpy.mod(h/6.0,1.0)

    hsv = numpy.asarray([h,s,v])
    
    return hsv

# =============================================================================
# hsv_to_rgb()
#
# hsv comes in as [h,s,v] with hue and saturation in the range [0,1],
# but value in the range [0,255].

def hsv_to_rgb( hsv ):

    h = hsv[0]
    s = hsv[1]
    v = hsv[2]

    #if s == 0.0: return v, v, v
    i = (h*6.0).astype(int)
    f = (h*6.0) - i
    p = v*(1.0 - s)
    q = v*(1.0 - s*f)
    t = v*(1.0 - s*(1.0-f))

    r = i.choose( v, q, p, p, t, v )
    g = i.choose( t, v, v, q, p, p )
    b = i.choose( p, p, t, v, v, q )

    rgb = numpy.asarray([r,g,b]).astype(numpy.uint8)
    
    return rgb

# =============================================================================
# Usage()

def Usage():
    print("""Usage: hsv_merge.py [-q] [-of format] src_color src_greyscale dst_color

where src_color is a RGB or RGBA dataset,
      src_greyscale is a greyscale dataset (e.g. the result of gdaldem hillshade)
      dst_color will be a RGB or RGBA dataset using the greyscale as the
      intensity for the color dataset.
""")
    sys.exit(1)
    
# =============================================================================
#     Mainline
# =============================================================================

argv = gdal.GeneralCmdLineProcessor( sys.argv )
if argv is None:
    sys.exit( 0 )

format = 'GTiff'
src_color_filename = None
src_greyscale_filename = None
dst_color_filename = None
quiet = False

# Parse command line arguments.
i = 1
while i < len(argv):
    arg = argv[i]

    if arg == '-of':
        i = i + 1
        format = argv[i]

    elif arg == '-q' or arg == '-quiet':
        quiet = True

    elif src_color_filename is None:
        src_color_filename = argv[i]

    elif src_greyscale_filename is None:
        src_greyscale_filename = argv[i]

    elif dst_color_filename is None:
        dst_color_filename = argv[i]
    else:
        Usage()

    i = i + 1

if dst_color_filename is None:
    Usage()

datatype = gdal.GDT_Byte

hilldataset = gdal.Open( src_greyscale_filename, gdal.GA_ReadOnly )
colordataset = gdal.Open( src_color_filename, gdal.GA_ReadOnly )

#check for 3 or 4 bands in the color file
if (colordataset.RasterCount != 3 and colordataset.RasterCount != 4):
    print('Source image does not appear to have three or four bands as required.')
    sys.exit(1)

#define output format, name, size, type and set projection
out_driver = gdal.GetDriverByName(format)
outdataset = out_driver.Create(dst_color_filename, colordataset.RasterXSize, \
                   colordataset.RasterYSize, colordataset.RasterCount, datatype)
outdataset.SetProjection(hilldataset.GetProjection())
outdataset.SetGeoTransform(hilldataset.GetGeoTransform())

#assign RGB and hillshade bands
rBand = colordataset.GetRasterBand(1)
gBand = colordataset.GetRasterBand(2)
bBand = colordataset.GetRasterBand(3)
if colordataset.RasterCount == 4:
    aBand = colordataset.GetRasterBand(4)
else:
    aBand = None

hillband = hilldataset.GetRasterBand(1)
hillbandnodatavalue = hillband.GetNoDataValue()

#check for same file size
if ((rBand.YSize != hillband.YSize) or (rBand.XSize != hillband.XSize)):
    print('Color and hilshade must be the same size in pixels.')
    sys.exit(1)

#loop over lines to apply hillshade
for i in range(hillband.YSize):
    #load RGB and Hillshade arrays
    rScanline = rBand.ReadAsArray(0, i, hillband.XSize, 1, hillband.XSize, 1)
    gScanline = gBand.ReadAsArray(0, i, hillband.XSize, 1, hillband.XSize, 1)
    bScanline = bBand.ReadAsArray(0, i, hillband.XSize, 1, hillband.XSize, 1)
    hillScanline = hillband.ReadAsArray(0, i, hillband.XSize, 1, hillband.XSize, 1)

    #convert to HSV
    hsv = rgb_to_hsv( rScanline, gScanline, bScanline )
    
    # if there's nodata on the hillband, use the v value from the color
    # dataset instead of the hillshade value.
    if hillbandnodatavalue is not None:
        equal_to_nodata = numpy.equal(hillScanline, hillbandnodatavalue)
        v = numpy.choose(equal_to_nodata,(hillScanline,hsv[2]))
    else:
        v = hillScanline

    #replace v with hillshade
    hsv_adjusted = numpy.asarray( [hsv[0], hsv[1], v] )
    
    #convert back to RGB
    dst_color = hsv_to_rgb( hsv_adjusted )

    #write out new RGB bands to output one band at a time
    outband = outdataset.GetRasterBand(1)
    outband.WriteArray(dst_color[0], 0, i)
    outband = outdataset.GetRasterBand(2)
    outband.WriteArray(dst_color[1], 0, i)
    outband = outdataset.GetRasterBand(3)
    outband.WriteArray(dst_color[2], 0, i)
    if aBand is not None:
        aScanline = aBand.ReadAsArray(0, i, hillband.XSize, 1, hillband.XSize, 1)
        outband = outdataset.GetRasterBand(4)
        outband.WriteArray(aScanline, 0, i)
    
    #update progress line
    if not quiet:
        gdal.TermProgress_nocb( (float(i+1) / hillband.YSize) )

转载于:https://www.cnblogs.com/gispathfinder/p/5790488.html