Noise negatively impacts the detection and characterization of lesions in mammography. While denoising filters may be used to suppress noise, they might also negatively affect the conspicuity of small lesions due to signal blurring and smearing. In previous works, we designed and validated a denoising pipeline, dedicated to mammography, capable of suppressing noise and avoiding excessive blur and smear. This is achieved by a fine-tuned noisy-denoised image blending step, which leverages a Poisson-Gaussian noise model. In the current work, we investigate the impact of the denoising pipeline on the localization of low contrast microcalcification clusters. To this end, a human observers study was conducted with a team of five medical physicists with experience in breast imaging. First, in the pilot study, we defined the limit of contrast for the localization task with and without the application of the denoising pipeline. Next, we investigated the effect of the denoising on the localization of microcalcification clusters. Clinical patient cases with dense breasts and simulated microcalcification clusters were used throughout this study to emulate challenging cases and to guarantee fine control over the lesion’s contrast. The results from six readers show that the limit of localization occurred at the contrasts 0.090 and 0.079 without and with denoising, respectively. The average correct localization rate was 77% and 81% without and with denoising, respectively. Thus, the results show that the readers were able to correctly locate significantly less conspicuous lesions (p<0.05), and also performed significantly better localizing microcalcification clusters (p<0.05) when the denoising pipeline was applied.