The principle and evaluation method of wavelet threshold denoising are analyzed aiming at the problem that Fourier transform cannot represent the abrupt change of image effectively and wavelet transform cannot represent the texture and slow change of image effectively in the process of image denoising. Through the quantitative comparison of Fourier image denoising and wavelet image denoising, a mixed Fourier-wavelet denoising algorithm is proposed based on the different characteristics of Fourier denoising and wavelet denoising. Experimental results show that the mixed wavelet algorithm is superior to simple Fourier denoising and wavelet denoising algorithm separately, which makes up for the disadvantages of the two algorithms, and has a good application prospect in the field of image denoising.
A passive, millimeter wave (MMW) and terahertz (THz) dual-band imaging system composed of 94 and 250 GHz single-element detectors was used to investigate preprocessing and fusion algorithms for dual-band images. Subsequently, an MMW and THz image preprocessing and fusion integrated algorithm (MMW-THz IPFIA) was developed. In the algorithm, a block-matching and three-dimensional filtering denoising algorithm is employed to filter noise, an adaptive histogram equalization algorithm to enhance images, an intensity-based registration algorithm to register images, and a wavelet-based image fusion algorithm to fuse the preprocessed images. The performance of the algorithm was analyzed by calculating the SNR and information entropy of the actual images. This algorithm effectively reduces the image noise and improves the level of detail in the images. Since the algorithm improves the performance of the investigated imaging system, it should support practical technological applications. Because the system responds to blackbody radiation, its improvement is quantified herein using the static performance parameter commonly employed for thermal imaging systems, namely, the minimum detectable temperature difference (MDTD). An experiment was conducted in which the system’s MDTD was measured before and after applying the MMW-THz IPFIA, verifying the improved performance that can be realized through its application.
The progress on terahertz imaging at Capital Normal University in Beijing is presented. Our works on
Terahertz Imaging include the active and passive imaging. For the active terahertz imaging, the pulse
and continue wave terahertz imaging are studied, respectively. The active terahertz pulse imaging is
based on the terahertz time-domain spectroscopy with the probe-beam-expanded femtosecond pulse
laser and an infrared CCD detection. The active terahertz continuous wave imaging is based on a
CO2-laser-pumped terahertz coherent source and a NEC terahertz camera. The active terahertz
polarization imaging is studied. For the passive terahertz imaging, the low frequency radiometers are
used to detect the beam-scanned terahertz signal by the point-to-point scanning. The related
components and image processing methods are developed and used for the improvement of imaging
speed and resolution.
Compared with microwave, THz has higher resolution, and compared with infrared, THz has better penetrability. Human body radiate THz also, its photon energy is low, it is harmless to human body. So THz has great potential applications in the body searching system. Dual-band images may contain different information for the same scene, so THz dual-band imaging have been a significant research subject of THz technology.
Base on the dual-band THz passive imaging system which is composed of a 94GHz and a 250GHz cell detector, this paper researched the preprocessing and fusion algorithm for THz dual-band images. Firstly, THz images have such problems: large noise, low SNR, low contrast, low details. Secondly, the stability problem of the optical mechanical scanning system makes the images less repetitive, obvious stripes and low definition. Aiming at these situations, this paper used the BM3D de-noising algorithm to filter noise and correct the scanning problem. Furthermore, translation, rotation and scaling exist between the two images, after registered by the intensity-base registration algorithm, and enhanced by the adaptive histogram equalization algorithm, the images are fused by image fusion algorithm based on wavelet. This effectively reduced the image noise, scan distortion and matching error, improved the details, enhanced the contrast. It is helpful to improve the detection efficiency of hidden objects too. Method in this paper has a substantial effect for improving the dual-band THz passive imaging system’s performance and promoting technology practical.
Terahertz (THz) imaging is a hot topic in the current imaging technology. THz imaging has the advantage to penetrate most of non-metal and non-polar materials for the detection of concealed objects, while it is harmless to biological organism. Continuous wave terahertz (THz) imaging is enable to offer a safe and noninvasive imaging for the investigated objects. In this paper, THz real-time polarization imaging system is demonstrated based on the SIFIR-50 THz laser as a radiation source and a NEC Terahertz Imager as an array detector. The experimental system employs two wire grid polarizers to acquire the intensity images in four different directions. The polarization information of the measured object is obtained based on the Stokes-Mueller matrix. Imaging experiments on the currency with water mark and the hollowed-out metal ring have been done. Their polarization images are acquired and analyzed. The results show that the extracted polarization images include the valuable information which can effectively detect and recognize the different kinds of objects.