This paper presents a new method to extract the envelope of the fundamental heart sound (S1 and S2) using the logistic function. The sigmoid characteristic of the logistic function is incorporated to segregate S1, and S2 signal intensities from silent or noise interfered systolic and diastolic intervals in a heart sound cycle. This signal intensity transformation brings uniformity to the envelope peak of S1 and S2 sound by inclining the transform intensity distribution towards the upper asymptote of the sigmoid curve. The proposed logistic function based amplitude moderation (LFAM) envelogram method involves finding the critical upper amplitude (xuc) above which the signals will be categorized as loud sound and the critical lower amplitude (xlc) below which the signal will be considered as noise. These critical values are regressively obtained from the signal itself by histogram analysis of intensity distribution. The performance is evaluated on noisy PCG dataset taken from PhysioNet/Computing in Cardiology Challenge 2016. The LFAM envelope yields better hill-valley discrimination of heart sounds from its silent/noisy signal intervals. The enhance heart sound envelope peaks are better than conventional methods. The proposed envelope feature is evaluated for heart sound segmentation using HSMM. There is a significant improvement in segmentation accuracy, especially at a low signal-to-noise ratio. The best average F1 score is 97.73%.