Noise removing belongs to image restoration in digital image processing. It’s the essential guarantee of identifying image information and the reliable guarantee of making further image processing. A satisfying result can’t be found if processing method such as feature extraction, registration or image fusion is carried out on an image with noise. So removing noise is absolutely necessary for i...

We present a novel shadow smoothing algorithm using the bilateral filter. From the observation that shadow leaking, which is found often in filter based approaches, occurs at depth discontinuity seen from the viewpoint of the eye, we apply the bilateral filter which is conceptually a product of two Gaussian filters, one for smoothing the shadow map and the other for handling depth discontinuity...

To exploit unknown ambient radio frequency signals of opportunity (SOPs) for positioning and navigation, one must estimate their states along with a set of parameters that characterize the stability of their oscillators. SOPs can be modeled as stochastic dynamical systems driven by process noise. The statistics of such process noise is typically unknown to the receiver wanting to exploit the SO...

Adaptive filters and image enhancement techniques have repeatedly been suggested to make feature extraction more robust. Few comparative analysis exists between competing techniques and even the existing ones evaluate only the effect of the filter on the image but not its effect on a feature extraction process. In this paper we present an experimental approach for the evaluation of low-level vi...

This paper studies the problem of designing robust H∞ filters for linear uncertain systems. The uncertainty parameters are assumed to be time-varying, unknown, but bounded, which appear affinely in the matrices of system models. An adaptive mechanism is introduced to construct novel filters with variable gains, which can reduce the conservativeness of traditional robust H∞ filters. The proposed...

This paper explores the use of imprecise computing to develop digital filters with adaptive length in order to meet real-time constraints. A large-order filter typically provides better filtering but takes longer to compute than a low order filter. An adaptive length filter can provide a resource manager with alternatives that can be used if resources become scarce. This paper discusses the use...

One of the main objectives within the adaptive signal processing is the noise suppression, i.e. the detection of information bearing signal in noise. Adaptive filter application ANC (Adaptive Noise Cancellation) using adaptive Filter algorithm is an important basis for signal processing. The device automatically filters out the components of the signal which are not related to the orignal signa...

An adaptive noise cancellation scheme for speech processing is described, in which adaptive filters operate in frequency–limited sub–bands. Previously the filters had been distributed in a linear fashion in the frequency domain. This work investigates the effects of spacing the filters more in sympathy with the signal power and spectral characteristics. It is found that improvements in signal–t...

An adaptive noise cancellation scheme for speech processing is proposed. In this, the adaptive filters are implemented in frequency–limited sub–bands. In previous work, the filters had been distributed in a linear fashion in the frequency domain. This work investigates the effects of spacing the filters more in sympathy with the signal power and spectral characteristics. It emerges that improve...

Adaptive nonlinear filtering plays an important role in audio signal processing and echo control. In this contribution a nonlinear system identification method is proposed. The setup is built using adaptive Volterra filters of second and third order with the same memory length. The adaptation is achieved using a Normalized Least Mean Square algorithm with a proper selected stepsize parameter fo...