Optical imaging remote sensing technology is an important technical means to obtain information of ground objects, but it is restricted by bad weather such as clouds, rain, and haze. In haze weather condition, optical images often have poor contrast and blurred details, which has a great impact on subsequent applications and interpretation. If the acquired images are processed, not only their quality can be improved, but also their visual effect and utilization value can be improved, so as to reduce the impact brought by haze. In general, the haze is removed from the view of image processing. In this paper, through in-depth analysis and study of existing algorithms and characteristics of optical remote sensing images, a new idea is proposed to solve this problem from the view of combination of image content and auxiliary information. Furthermore, a new haze removal algorithm is proposed based on the Retinex multi-scale model and the histogram characteristics of remote sensing images. Because the new method combines multi-scale model (MSM) and histogram characteristics (HC), it is referred to as MSMHC algorithm in this paper. The advantage of the new method is that the content and type of image are considered in the whole process, and then two processing schemes are set for haze removal. In the test experiments, one hundred groups of image data were used to carry out comparative experiments. At the same time, single-scale Retinex (SSR) algorithm, multi-scale Retinex (MSR) algorithm, dark channel priori (DCP) method, brightness preserving dynamic fuzzy histogram equalization (BPDFHE) algorithm, histogram equalization (HE) method, and homomorphic filter (HF) algorithm were used for comparative experiments with the MSMHC method. Five parameters, including standard deviation (SD), information entropy (IE), peak signal to noise ratio (PSNR), structural similarity (SSIM), and image contrast (IC), were used to quantitatively evaluate the test results. The experimental results and the parameter values showed that the MSMHC algorithm could not only effectively remove haze from remote sensing images, obtain high contrast and high definition images, but also have better generalization ability.

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Haze Removal Algorithm for Optical Remote Sensing Image Based on Multi-Scale Model and Histogram Characteristic

The enhancement of catenary image with low visibility based on multi-feature fusion network in railway industry

The invention discloses a biorthogonal polarization multiplexing intensity modulation system and a demultiplexing method thereof. According to the system, two paths of orthogonal polarization multiplexing intensity modulation optical signals are connected to one optical coupler together; and the optical coupler, a wavelength division multiplexer, an optical amplifier, an optical fiber, a wavelength division demultiplexer, a stokes analyzer and a digital signal processing unit are sequentially connected. The method comprises the steps of: at a transmitting terminal, generating double orthogonal polarization state multiplexed signals, and by a polarization controller and the optical coupler, multiplexing the signals together at different polarization angles; at a receiver terminal, by using the stokes analyzer as a receiving mode, obtaining electric signals I0, I0deg, I45deg and IRC; implementing demodulation and recovery of the multiplexed signals by utilizing real-time DSP (Digital Signal Processing); and the like. According to the biorthogonal polarization multiplexing intensity modulation system and the demultiplexing method thereof, which are disclosed by the invention, when flexibility of the transmitting terminal and the receiver terminal in an optical network is ensured, the structure of the receiver terminal is simplified, communication capacity is multiplied, and cost is reduced.

Biorthogonal polarization multiplexing intensity modulation system and demultiplexing method thereof

We present white balancing, quad-tree decomposition, and L 1 minimization-based dehazing technique. Atmospheric light is estimated through quad-tree decomposition while holistic transmission map is estimated through coarse-scale net. Coarse and fine layers are refined through fusion and a luminance model is used to preserve details and edges. The final dehazed image is refined using L 1 minimization. Simulation results when equated with existing techniques, verify the effectiveness of the proposed technique.

White balancing, quad-tree decomposition, and L1 minimization-based single-image dehazing

The invention discloses a synchronizing signal transmitting-receiving device and method based on faster than Nyquist filtering. The method comprises the following steps: performing faster than Nyquistfiltering on a plurality of paths of input synchronizing signals at a transmitting end, and aggregating a plurality of paths of filtering signals into one path of high-speed aggregation signal; amplifying the obtained aggregation signal; modulating the amplified aggregation signal into an optical signal and transmitting the optical signal; converting the received optical signal into an electricalsignal at a receiving end to obtain one path of aggregation signal; amplifying the obtained aggregation signal; and decomposing one path of amplified high-speed aggregation signal into a plurality ofpaths of signals, and performing faster than Nyquist decoding on each path of signal respectively to obtain a plurality of paths of synchronizing signals. Through adoption of the synchronizing signaltransmitting-receiving device and method, the transmission and receiving of a plurality of paths of high-speed synchronizing signals are realized; partial overlapping of synchronizing signal spectrums of adjacent channels is supported; and high spectrum efficiency is achieved. Moreover, inter-channel crosstalk caused by spectrum overlapping is lowered effectively through faster than Nyquist filtering; the implementation way is simple; and the calculation complexity is relatively low.

Synchronizing signal transmitting-receiving device and method based on faster than Nyquist filtering

Instant haze removal from a single image

The invention discloses an optical modulation method in combination of an I-class partial response pulse forming technique and dual-polarization 16 QAM (Quadrature Amplitude Modulation) and a corresponding demodulation method thereof. The optical modulation method comprises following steps: converting binary data of homonymous I and Quadrature Q branches of two polarization states into quanternary data signals; generating shaped base band signals through I-class partial response pulse shaping filter; and modulating an IQ quadrature modulator, thus obtaining modulated signals. The grid chart adopted in VA-based MLSD detection by the corresponding demodulation method is obtained by utilizing correlations of front and back code elements; the demodulation method is effective and feasible; according to the methods disclosed by the invention, the I-class partial response pulse forming technique is combined with the DP-16 QAM; regular and processible intersymbol interferences are imported; compared with the16 QAM in combination of Nyquist shaping filter, the signal bandwidth is further compressed; the transmission in an ultra-Nyquist wavelength division multiplexing system is realized; and the frequency utilization rate and transmission capacity of the system are improved.

Nan Zhao

Papers

Instant haze removal from a single image

Optical modulation method based on ultra-Nyquist system and corresponding demodulation method thereof