Adaptive filter in image processing

Adaptive filters are commonly used in image processing to enhance or restore data by removing noise without significantly blurring the structures in the image. The adaptive filtering literature is vast and cannot adequately be summarized in a short chapter.

1. What is meant by adaptive filter?
2. What is adaptive spatial filtering?
3. What is adaptive filtering in neural networks?
4. What is adaptive filter in noise cancellation?

What is meant by adaptive filter?

Adaptive filters are digital filters whose coefficients change with an objective to make the filter converge to an optimal state. The optimization criterion is a cost function, which is most commonly the mean square of the error signal between the output of the adaptive filter and the desired signal.

What is adaptive spatial filtering?

An adaptive spatial filtering for images is presented with application to postprocessing of block coding images. The main purpose is to reduce the degradation in decoded images caused by block coding with no increase in the bit-rate of coding. The filter design is based on some prior knowledge about image edges, D.

What is adaptive filtering in neural networks?

An adaptive filter automatically adjusts Its own Impulse response. In this paper adaptive noise canceller and adaptive signal enhancer systems are implemented using feedforward and recurrent neural networks using back propagation algorithm and real time recurrent learning algorithm respectively for training.

What is adaptive filter in noise cancellation?

The adaptive noise cancellation system assumes the use of two microphones. A primary microphone picks up the noisy input signal, while a secondary microphone receives noise that is uncorrelated to the information bearing signal, but is correlated to the noise picked up by the primary microphone.