We propose a series of procedures to construct an image as similar as possible to that detected in good illumination conditions (standard image), starting from a low light level (L3) image. In L3 conditions, only a small number of photopulses are detected in the whole image area. An image taken in these conditions appears like a few isolated light points over a dark background. This makes it nearly impossible to recognize an object represented on it. We have developed a method based on the L3 image statistics in order to estimate the intensity received by each pixel. This method consist of a spatial average performed by a photon counting mask and can be used to construct a standard image from only one L3 image. As a second step, we have studied some histogram operations to eliminate the heavy statistics dependence that remains in the post-mask image. The best results correspond to the histogram specification but, to perform it, it would be necessary to know the standard image histogram. The last step of our work is the development of a fitting method to obtain this standard image histogram. This fitting is based on the statistical behavior of the L3 image and can be done using only a post-mask histogram as data.