To avoid grabbing the unintentional user motion in a video sequence, video stabilization techniques are used to obtain better-looking video for the final user. We present a low power rototranslational solution, extending our previous work specifically addressed for translational motion only. The proposed technique achieves a high degree of robustness with respect to common difficult conditions like noise perturbations, illumination changes, and motion blurring. Moreover, it is also able to cope with regular patterns, moving objects and it is very precise, reaching about 7% of improvement in jitter attenuation, compared to previous results. Overall performances are competitive also in terms of computational cost: it runs at more than 30 frames / s with VGA sequences, with a CPU ARM926EJ-S at just 100 MHz clock frequency.
Despite the great advances that have been made in the field of digital photography and CMOS/CCD sensors, several
sources of distortion continue to be responsible for image quality degradation. Among them, a great role is played by
sensor noise and motion blur. Of course, longer exposure times usually lead to better image quality, but the change in the
photocurrent over time, due to motion, can lead to motion blur effects. The proposed low-cost technique deals with the
aforementioned problem using a multi-capture denoising algorithm, obtaining a good quality with sensible reduction of
the motion blur effects.
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.
New approaches to Color Interpolation based on Discrete Wavelet Transform are described. The Bayer data are split into the three colour components; for each component the Wavelet Coefficient Interpolation (WCI) algorithm is applied and results are combined to obtain the final colour interpolated image. A further anti-aliasing algorithm can be applied in order to reduce false colours. A first approach consists of interpolating wavelet coefficients starting from a spatial analysis of the input image. It was considered an interpolation step based on threshold levels associated to the spatial correlation of the input image pixel. A second approach consists of interpolating wavelet coefficients starting from the analysis of known coefficients of the second transform level. The resolution of each wavelet transform level is double as regards the successive one, so we can suppose a correspondence among wavelet coefficients belong to successive sub-bands. Visual quality of the interpolated RGB images is improved, reducing the zipper and aliasing effects. Moreover, in an embedded systems, which use JPEG2000 compression, a low computational cost is achieved in both cases since only some threshold evaluations and the IDWT step are performed for the first approach, while the second one involves only the DWT and IDWT steps.