The abnormal function of cells can be detected by anatomic or physiological registrations. Most of modern approaches, as ultrasound, RMN or CT, show anatomic parametric modifications of tissues or organs. They highlight areas with a larger diameter 1 cm. In the case of skin or superficial cancers, local temperature is different, and it can be put out by thermal imager. Medical imaging is a leading role in modern diagnosis for abnormal or normal tissues or organs. Some information has to be improved for a better diagnosis by reducing or removing some unwanted information like noise affecting image texture. The traditional technologies for medical image enhancement use spatial or frequency domain methods, but whole image processing will hide both partial and specific information for human signals. A particular kind of medical images is represented by thermal imaging. Recently, these images were used for skin or superficial cancers diagnosis, but very clear outlines of certain alleged affected areas need to be shown. Histogram equalization cannot highlights the edges and control the effects of enhancement. A new filtering method was introduced by Huang by using the empirical mode decomposition, EMD. An improved filtering method for thermal images, based on EMD, is presented in this paper, and permits to analyze nonlinear and non-stationary data by the adaptive decomposition into intrinsic mode surfaces. The results, evaluated by SNR ratios, are compared with other filtering methods.
Modern radars must provide in a very short time: existence, mobility and shape of objects evolving in airspace. Evaluation of the object shapes through active research by using synthetic aperture radar is limited in time, resolution, and cost. A new way of processing non-stationary signals is presented in this article. Signals are obtained from the reflection of the electromagnetic field by objects with complex shape when they are irradiated with linear frequency modulated signals. The amplitude of reflected signal is variable on the radio-impulse duration depending on object shape, causing a certain electromagnetic signature. This phenomenon is caused by specific electromagnetic resonance. The reflected signal has maximum amplitude when the frequency of the incident wave is the same with the resonant frequency of the investigated object. The structure of an radar target can be decomposed into simple geometric shapes such as spheres, ellipsoids, prisms, and so on. Using resonant effect that ensures pattern recognition is exemplified by an object with an aerodynamic profile accepted in many component elements of the aircraft, namely - an ellipsoid. It is a geometric shape used extensively in aviation, because it has a very low aerodynamic resistance. The resonant response of ellipsoid is evaluated in a decade frequency band, but the pattern recognition of this shape is enough for an octave band. The resonant response is assessed for cross polarization of incident electromagnetic field, as well. As a result, the radio-impulse shape can be used in a data base for pattern recognition.
The development of the information technology and computer networks facilitates easy duplication, manipulation, and distribution of digital data. Digital watermarking is one of the proposed solutions for effectively safeguarding the rightful ownership of digital images and video. We propose a public digital watermarking technique for video copyright protection in the discrete wavelet transform domain. The scheme uses binary images as watermarks. These are embedded in the detail wavelet coefficients of the middle wavelet subbands. The method is a combination of spread spectrum and quantization-based watermarking. Every bit of the watermark is spread over a number of wavelet coefficients with the use of a secret key by means of quantization. The selected wavelet detail coefficients from different subbands are quantized using an optimal quantization model, based on the characteristics of the human visual system (HVS). Our HVS-based scheme is compared to a non-HVS approach. The resilience of the watermarking algorithm is tested against a series of different spatial, temporal, and compression attacks. To improve the robustness of the algorithm, we use error correction codes and embed the watermark with spatial and temporal redundancy. The proposed method achieves a good perceptual quality and high resistance to a large spectrum of attacks.