Added demos: Histogram Equalization and RGB to Grayscale conversion

docs/examples/color_channels/rgb_grayscale.jl

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+# ---
+# title: RGB to GrayScale
+# cover: assets/rgb_grayscale.png
+# ---
+
+# This example illustrates RGB to Grayscale Conversion
+
+
+using Images, TestImages
+
+rgb_image = testimage("lighthouse")
+
+# I = Gray.(RGB) converts an RGB image to Grayscale. 
+
+gray_image = Gray.(rgb_image)
+hcat(rgb_image, gray_image)
+
+# Gray scale conversion form RGB follows a weighted sum of all channels, the coffecients are computed according to
+# [Rec. ITU-R BT.601-7](https://www.itu.int/dms_pubrec/itu-r/rec/bt/R-REC-BT.601-7-201103-I!!PDF-E.pdf) rounding off to 3 decimal places 
+# `0.299 * R + 0.587 * G + 0.114 * B`
+
+save("assets/rgb_grayscale.png", gray_image) #src

docs/examples/spatial_transformation/histogram_equalization.jl

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+# ---
+# title: Histogram equalisation
+# cover: assets/histogram_equalization.png
+# ---
+
+# This demo issustrates the use of [Histogram equalization](https://juliaimages.org/ImageContrastAdjustment.jl/stable/reference/#Equalization-1), [gamma correction matching](https://juliaimages.org/ImageContrastAdjustment.jl/stable/reference/#Matching-1)
+# and [Contrast Limited Adaptive Histogram Equalization](https://juliaimages.org/ImageContrastAdjustment.jl/stable/reference/#AdaptiveEqualization-1)
+
+# Histogram equalisation is used to imporve the contrast in an
+# single-channel grayscale image. It distributes the intensity of the image
+# in a uniform manner. The natural justification for uniformity
+# is that the image has better contrast if the intensity levels of an image span
+# a wide range on the intensity scale. The transformation is based on mapping of
+# cumulative histogram
+
+using ImageContrastAdjustment, TestImages
+
+img = testimage("moonsurface")
+
+# Now we will apply Histogram equalisation, gamma correction and Adaptive histogram equalisation 
+# method to enhance contrast of the image
+
+hist_equal = adjust_histogram(img, Equalization(nbins = 256))
+gamma_correction = adjust_histogram(img, GammaCorrection(gamma = 2))
+hist_adapt = adjust_histogram(img, AdaptiveEqualization(nbins = 256, rblocks = 4, cblocks = 4, clip = 0.2))
+
+hcat(img, hist_equal, gamma_correction, hist_adapt)
+
+# --- save covers --- #src
+using Images #src
+save("assets/histogram_equalization.png", hist_equal) #src