Giuseppe Spampinato

Fast method for noise level estimation and integrated noise reduction

This paper describes a fast method for noise level estimation and denoising. Specifically, we address the problem of estimating the standard deviation of additive white Gaussian noise in digital images; the computed value is used to reduce Gaussian noise and eliminate defective pixels in a raw digital image. The method is particularly suitable for implementation in low power mobile devices with imaging capabilities such as camera phones, as well as digital still cameras (DSC).

Temporal noise reduction of Bayer matrixed video data

This paper describes a new approach for noise reduction of video sequences that directly processes raw data frames acquired by an image sensor. The proposed noise reduction filter operates on Bayer matrixed video sequences instead of the canonical YUV format allowing saving of resources in terms of time and space; this is particularly relevant for real time processing. Noise level is constantly monitored in order to change the filter strength adaptively. Experiments show the effectiveness of the proposed approach.

Chroma noise reduction in DCT domain using soft-thresholding

The chroma noise effect seriously reduces the quality of digital images and videos, especially if they are acquired in low-light conditions. This paper describes the DCT-CNR (Discrete Cosine Transform-Chroma Noise Reduction), an efficient chroma noise reduction algorithm based on soft-thresholding. It reduces the contribution of the DCT coefficients having highest probability to be corrupted by noise and preserves the ones corresponding to the details of the image. Experiments show that the proposed method achieves good results with low computational and hardware resources requirements.

Adaptive color bleeding removal for video and still DCT compressed sequences

DCT based compression engines1,2 are well known to introduce color artifacts on the processed input frames, in particular for low bit rates. In video standards, like MPEG-23, MPEG-44, H2635, and in still picture standards, like JPEG6,7, blocking and ringing distortions are understood and considered, so different approaches have been developed to reduce these effects8,9,10,11. On the other side, other kinds of phenomenon have not been deeply investigated. Among them, the chromatic color bleeding effects has only recently received proper attention12,13. The scope of this paper is to propose and describe an innovative and powerful algorithm to overcome this kind of color artifacts.

Efficient error handling for video and still picture standards

This paper describes new methods for errors handling at the decoder side, when channel noise affects the transmission of the compressed stream. The proposed error detection techniques are applied to MPEG-4 standard video, but can be also used for general video and still picture standards in which inverse quantization clipping or resynchronization markers are present as MPEG-2, H263, H261, JPEG and JPEG2000. The improved error concealment techniques presented can be extended to all the standards in which reverse variable length coding is present.

Advanced feature based digital video stabilization

The present paper describes a low-cost algorithm for video stabilization. Like other feature based algorithms, it is robust to motion blur, noise and illumination changes. Moreover, maintaining real time processing, it is not negatively affected by moving objects in the scene, works fine even in conditions of low details in the background and it is robust to scene changes.

Camera shaking effects reduction by means of still sequence stabilization and spatio-temporal filtering

Even if it is believed that in the near future optical image stabilization will be mounted on mobile consumer devices, thus providing a reliable and fast way to deal with camera shaking problems, for the time being, under critical acquisition conditions, handheld captured photography suffers from motion blur effects. This article summarizes a low-cost digital technique to deal with the aforementioned problem employing a mixture of multi-capture, algorithmic stabilization and de-noising techniques.

JPEG Adaptive Chromatic Post-Processing

In last years, different types of colour artifacts, overall blocking and ringing, have been deeply investigated. In this paper we focus the attention on chromatic color bleeding effects. This phenomenon is evident in DCT based compression engines. In our work we investigate the possibility to implement a color bleeding removal by means of adaptive filtering. Simulation results and visual impacts show the improvement of color fidelity of the proposed post- processing scheme.

Improved color interpolation using discrete wavelet transform

Single-chip digital color cameras use a Color Filter array (CFA) to capture images. The Bayer Color Array is one of the commonly used. Colors are sub-sampled and mosaicked, so an estimation of missing colors is required in the points where the sample is not acquired. Starting from Revathi-Raju-Nayar zooming images technique in the Wavelet domain, we present novel approaches to Color Interpolation based on Discrete Wavelet Transform (DWT) coefficients interpolation. Most demosaicing algorithms obtain a good color fidelity, but they often reach a trade-off between sharp images and the so called “zipper effect”. Results shows that the proposed methods give good reconstruction quality, with smaller visual effects compared to other methods. We discuss the theory behind our approach and we show experimentally the theoretic advantages obtained improving visual quality. Furthermore, in embedded systems using JPEG2000 compression, a low computational cost is achieved thanks to the availability of the DWT step.

Fast and Low Power Consumption Outliers Removal for Motion Vector Estimation

When in a pipeline a robust global motion estimation is needed, RANSAC algorithm is the usual choice. Unfortunately, since RANSAC is an iterative method based on random analysis, it is not suitable for real-time processing. This paper presents an outlier removal algorithm, which reaches a robust estimation at least equal to RANSAC with really low power consumption and can be employed for embedded time implementation.