Colour is widely used in remote sensing work. In many instances, the use of colour conveys additional information both visually and scientifically. Remote sensing satellites view the earth in different spectral bands, viz. near infrared (NIR), red, green, and blue bands, in a conventional multispectral imaging system. In the absence of a blue channel, colour images can be generated using near infrared, red, and green bands in what is known as a false colour composite (FCC) and does not look natural, like the image we see with the naked eye. For a trained interpreter, this does not pose any problems. However, when the intended use is a fly-through of a draped terrain, visual interpretation, or a display, meant for the non-remote sensing professional, this becomes a handicap. To overcome this, there is a requirement to generate natural colour composites (NCC) from the given false colour composite, which demands the simulation of a blue band to be combined with green and red bands. This paper describes a unique method of generating a blue band to form natural colour images from a given false colour image set. We use a spectral transformation method to establish a relationship between the false colour and true colour image pairs provided by a sensor with all the four bands, which has a broader spectral coverage. A transformation function is fitted by selecting radiometric control points along the line of geometric registration to find a set of coefficients to be used for simulating a blue band. This blue band, along with the green and red bands, provides a near true colour or 'natural colour' on the display. In this paper, we present a set of adjustable radiometric transformation coefficients to accommodate variation in spatial and dynamic range offered by sensors to generate natural colour. These coefficients seem to work on a large number of images of different seasons, provided similar spectral bands and terrain are used. The proposed 'natural colour generator' can be used in changing false colour images to natural colour images with the aim of 'what you get is what you would have seen'.

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