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Objectives: In this work, a simple technique to assess the image quality characteristics of the postprocessed image is developed and an easy to use figure of image quality (FIQ) is introduced. This FIQ characterizes images in terms of resolution and noise. In addition information capacity, defined within the context of Shannon's information theory, was used as an overall image quality index., Materials and Methods: A digital mammographic image was postprocessed with three digital filters. Resolution and noise were calculated via the Modulation Transfer Function (MTF), the coefficient of variation, and the figure of image quality. In addition, frequency dependent parameters such as the noise power spectrum (NPS) and noise equivalent quanta (NEQ) were estimated and used to assess information capacity., Results: FIQs for the "raw image" data and the image processed with the "sharpen edges" filter were found 907.3 and 1906.1, correspondingly. The information capacity values were 60.86 × 10(3) and 78.96 × 10(3) bits/mm(2)., Conclusion: It was found that, after the application of the postprocessing techniques (even commercial nondedicated software) on the raw digital mammograms, MTF, NPS, and NEQ are improved for medium to high spatial frequencies leading to resolving smaller structures in the final image.