Abstract
The storage of colour information in a greyscale image is not a new idea. Various techniques have been proposed using different colour spaces including the standard RGB colour space, the YUV colour space, and the YCbCr colour space. This paper extends the results described in [1] and [2]. While [1] describes the storage of colour information in a greyscale image using Haar wavelets, and [2] adds a comparison with Kekre’s wavelets, this paper adds a third transform – the Walsh transform and presents a detailed comparison of the performance of all three transforms across the LUV, YCbCr, YCgCb, YIQ, and YUV colour spaces. The main aim remains the same as that in [1] and [2], which is the storage of colour information in a greyscale image known as the “matted” greyscale image.
Highlights
The efficient storage of colour images in digital format has always been a dilemma faced when working with many, high resolution, digital images
When considering only the matted greyscale images, all three transforms perform adequately well; when taking into consideration the reconstructed colour image, as has been the norm, the Walsh transform‟s reconstructed image is significantly inferior to those using the Haar transform and the Kekre‟s Wavalet Transform (KWT)
After applying the technique to embed colour information in a greyscale image using various colour spaces and three transforms and studying the results obtained, it can be safely concluded that the Walsh transform should not be considered as an appropriate transform to implement this algorithm
Summary
The efficient storage of colour images in digital format has always been a dilemma faced when working with many, high resolution, digital images. Unlike the storage problem mentioned above, this one is much harder to solve since it entails the extraction of more information from a source that has less information, i.e. the retrieval of colour (multi-plane) information from a greyscale (single-plane) source This is, by definition, not directly possible – how can one create information when none exists? This problem needs a more indirect solution – the missing information needs to be provided either externally (separated from the greyscale image to be coloured), or somehow embedded as “extra” information in the greyscale image itself Examples of the former can be found in [3], [4], [5], and [6]. Multi-plane (colour) data is “compressed” into a single-plane (greyscale)
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