Audio coding and image denoising based on the nonuniform modulated complex lapped transform

Xiong and Malvar recently introduced a nonuniform modulated complex lapped transform (NMCLT) with good time-localization and controllable frequency resolution by using an oversampled nonuniform filter bank to generate its real and the imaginary components. In this paper, we first show that oversampling in the NMCLT is not necessary in theory but a by-product of fast implementation in practice. We also point out that the amount of oversampling, which can be flexibly controlled, depends on the application. We then describe in detail the implementation of the inverse transform, which was not addressed clearly by Xiong and Malvar. We present the first applications of the NMCLT to audio coding and image denoising. A scalable audio coder has been implemented by controlling the amount of oversampling and exploiting redundancy among the NMCLT coefficients via predictive coding. Experimental results show that the audio coder reduces pre-echoes and improves the sound quality of audio clips with transient sounds. A simple denoising algorithm based on the NMCLT has also been devised to provide images with better visual quality than those obtained with wavelet-based soft thresholding.