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We investigated the representation of a wide range of colours in the lateral geniculate nucleus (LGN) of macaque monkeys. We took an approach to reconstruct a colour space from responses of a population of neurons. We found that, in the derived colour space (`LGN colour space'), red and blue regions were compressed whereas purple region was expanded, compared with those in a linear cone-opponent colour space. We found that the expanding/compressing pattern in the LGN colour space was related to the colour histogram derived from a natural image database. Quantitative analysis showed that the response functions of the population of the neurons were nearly optimal according to the principle of 'minimizing errors in estimation of stimulus colour in the presence of response noise'. Our findings support the idea that the colour representation at the early neural processing stage is adapted for efficient coding of colour information in the natural environment.