This study focuses on hexagonally sampled images and grayscale morphology. We combine hexagonal image processing and grayscale morphology to develop hexagonal grayscale morphology, and propose an algorithm to detect and enhance edges. Hexagonal image processing consists of three important steps: conversion of hexagonally sampled images, processing, and display of processed images on simulated hexagonal grid. We construct four different sizes of hexagonal structuring elements to apply morphological operations on hexagonal images. In this study, we applied morphological gradient for edge detection and proposed algorithm for edge enhancement. Moreover, we developed six different shapes of structuring elements to find an optimum one. Finally, we assessed two methods to compare our results, and identified the best result and optimum structuring element. We expect that proposed algorithm will offer a useful tool of image processing on hexagonally sampled images.