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An algorithm has been developed to isolate the gravity waves (GWs) of different scales from airglow images. Based on the discrete wavelet transform, the images are decomposed and then reconstructed in a series of mutually orthogonal spaces, each of which takes a Daubechies (db) wavelet of a certain scale as a basis vector. The GWs in the original airglow image are stripped to the peeled image reconstructed in each space, and the scale of wave patterns in a peeled image corresponds to the scale of the db wavelet as a basis vector. In each reconstructed image, the extracted GW is quasi-monochromatic. An adaptive band-pass filter is applied to enhance the GW structures. From an ensembled airglow image with a coverage of 2100 km × 1200 km using an all-sky airglow imager (ASAI) network, the quasi-monochromatic wave patterns are extracted using this algorithm. GWs range from ripples with short wavelength of 20 km to medium-scale GWs with a wavelength of 590 km. The images are denoised, and the propagating characteristics of GWs with different wavelengths are derived separately.

Extraction of Quasi-Monochromatic Gravity Waves from an Airglow Imager Network