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The recombination rate of markers far away from the candidate gene in the F2 and BC1P1 population. (DOCX 13 kb)

Supplementary 1. Sequences of W1827 and P1835. (DOC 29 kb)

As Empirical Mode Decomposition(EMD) and Local Mean Decomposition(LMD) cannot take care of both the decomposition rate and the smallest error simultaneously,a fast and effective method combined Piecewise Cubic Hermite Interpolating Polynomial with the LMD(PCHIP-LMD) was proposed to improve the precision of iris recognition.According to the distribution characteristics of iris textures,the PCHIP-LMD method was used to decomposed a normalized recognition image line by line to generate the component image with different scales.Then,the feature image of iris was obtained by binarization of useful components for the iris recognition.Furthermore,the Hamming distance was used to match the feature image by horizontal and vertical shifts to obtain the matched vectors.Finally,the improved standard deviation of the matching vector was calculated and was used to iris recognition.This method was used in CASIA1.0、CASIA2.0、CASIA3.0-Interval and MMU1 database and obtained results show that the correct recognition rates are achieved respectively 99.968 1%,99.884 5%,99.993 5%,99.878 2%.These experimental results demonstrate that the proposed method eliminates the high frequency noise when the iris feature is extracted and obtains the binary feature of the image effectively,which have the advantages of higher speeds,higher recognition rates and better robustness.

For the low infrared image contrast and high background noise, we proposed a new image fusion algorithm based on lifting stationary wavelet multi-scale product. The high-frequency coefficient option based on edges gradient energy was proposed based on lifting stationary wavelet multi-scale product, which makes full use of multi-scale product features with enhancing edges structure while weakening image noise; The weighted method was used for low-frequency coefficients fusion. Then wavelet transform reconstruction was realized to get the final fused image. Experimental results show that the algorithm can better protect edge features and all the useful information of the source images while restraining noise. The better visual effects are gained compared with the traditional fusion methods.

In allusion to requirement of real time and high accuracy in airborne image aided navigation system an algorithm based on robust Hausdorff distance of airborne remote image real time matching is put forward. Because of great information in remote image at first wavelet transform is used to acquire low frequency component to realize image compression to decrease calculation work and increase matching speed, and modified invariant moment is done to correct image distortion, then robust Hausdorff distance is used to realize remote image real time matching to acquire high matching precision, simulative experiment is done. Simulative experiment proves that the matching of a remote sensing image and a template image can be fulfilled about 1.6 second, the algorithm is robust and effective, and real time image navigation can be achieved.

In allusion to requirement of real time high precision matching of remote image in airborne image aided navigation system rotation resistance airborne remote image real time matching algorithm is put forward to eliminate noise and geometrical aberrance. Because of great information in remote image at first Harris corner detection algorithm is used to extract character point of remote image to increase matching speed, and modified invariant moment is done to correct image distortion caused by different time, different view angel, different sensor and so on; then robust Hausdorff distance is used to realize remote image real time matching to acquire high matching precision, then simulative experiment is done on airborne image acquired by sensor or radar and digital map stored in computer at last. Simulative experiment indicates that image matching rate of rotation resistance algorithm is better than algorithm which is not adopted modified invariant moment, and the algorithm is available and effective.

In allusion to the character of aircraft orientation error in inertial navigation system increasing with its working time and error accumulation, airborne image aided navigation system is imported in inertial navigation system to combine integrated navigation system. To acquire high orientation accuracy and high matching speed a new algorithm based on multi-scale edge detection and generalized point theory is put forward. At first multi-scale edge detection algorithm is adopted to realize airborne image edge detection, then image matching algorithm is used based on generalized point theory is used to eliminate error accumulation of peg-top excursion and accelerometer error to correction aircraft aircraft pose error to increase navigation accuracy of aircraft. To prove the algorithm is effective and robust, simulative experiment is done. The simulative experiment indicated that aircraft orientation accuracy is better than inertial navigation system, and its orientation error is less than 15 meters after airborne image aided navigation correction.