Made teas and typical tea-grown soils in Sichuan and Chongqing were collected to investigate soil nutrients, related soil properties and tea quality. The tea-grown soils in Sichuan and Chongqing are distributed mainly...Made teas and typical tea-grown soils in Sichuan and Chongqing were collected to investigate soil nutrients, related soil properties and tea quality. The tea-grown soils in Sichuan and Chongqing are distributed mainly in mountainous areas. The high annual precipitation (over 1100 mm), precipitous soil slopes, low cohesion among soil particles and high soil porosity suggested that intensive erosion and leaching might occur in these soils. Moreover, they were very acidic and poor in mineral nutrients such as N, P, K, Ca and Mg except S. The average content of total S was 20.40 g kg-1, much higher than that of organic matter in these soils, revealing that S in the tea-grown soils existed mainly in inorganic forms and very little in organic forms. Water-extractable S accounted for only a small amount of total S, which showed that most parts of sulfur in these soils were insoluble in W8ter. K and S varied greatly in made teas. The concentrations of N and P, however, varied little in these teas even though they differentiated significantly in the tea-grown soils. The high concentration of nitrogen in made teas could result in the high free amino acids and low polyphenol of teas. Significantly positive correlation was established between potassium and polyphenol in made teas. Teas with high ratio of phenol to free amino acids were usually good in taste and appearance.展开更多
Video reconstruction quality largely depends on the ability of employed sparse domain to adequately represent the underlying video in Distributed Compressed Video Sensing (DCVS). In this paper, we propose a novel dyna...Video reconstruction quality largely depends on the ability of employed sparse domain to adequately represent the underlying video in Distributed Compressed Video Sensing (DCVS). In this paper, we propose a novel dynamic global-Principal Component Analysis (PCA) sparse representation algorithm for video based on the sparse-land model and nonlocal similarity. First, grouping by matching is realized at the decoder from key frames that are previously recovered. Second, we apply PCA to each group (sub-dataset) to compute the principle components from which the sub-dictionary is constructed. Finally, the non-key frames are reconstructed from random measurement data using a Compressed Sensing (CS) reconstruction algorithm with sparse regularization. Experimental results show that our algorithm has a better performance compared with the DCT and K-SVD dictionaries.展开更多
In order to improve depth extraction accuracy, a method using moving array lenslet technique(MALT) in pickup stage is proposed, which can decrease the depth interval caused by pixelation. In this method, the lenslet a...In order to improve depth extraction accuracy, a method using moving array lenslet technique(MALT) in pickup stage is proposed, which can decrease the depth interval caused by pixelation. In this method, the lenslet array is moved along the horizontal and vertical directions simultaneously for N times in a pitch to get N sets of elemental images. Computational integral imaging reconstruction method for MALT is taken to obtain the slice images of the 3 D scene, and the sum modulus(SMD) blur metric is taken on these slice images to achieve the depth information of the 3 D scene. Simulation and optical experiments are carried out to verify the feasibility of this method.展开更多
基金Project supported by the Dept. of Agricultural Science, Potassium Commercial Association, Azote, France and the Municipal Scienc
文摘Made teas and typical tea-grown soils in Sichuan and Chongqing were collected to investigate soil nutrients, related soil properties and tea quality. The tea-grown soils in Sichuan and Chongqing are distributed mainly in mountainous areas. The high annual precipitation (over 1100 mm), precipitous soil slopes, low cohesion among soil particles and high soil porosity suggested that intensive erosion and leaching might occur in these soils. Moreover, they were very acidic and poor in mineral nutrients such as N, P, K, Ca and Mg except S. The average content of total S was 20.40 g kg-1, much higher than that of organic matter in these soils, revealing that S in the tea-grown soils existed mainly in inorganic forms and very little in organic forms. Water-extractable S accounted for only a small amount of total S, which showed that most parts of sulfur in these soils were insoluble in W8ter. K and S varied greatly in made teas. The concentrations of N and P, however, varied little in these teas even though they differentiated significantly in the tea-grown soils. The high concentration of nitrogen in made teas could result in the high free amino acids and low polyphenol of teas. Significantly positive correlation was established between potassium and polyphenol in made teas. Teas with high ratio of phenol to free amino acids were usually good in taste and appearance.
基金supported by the Innovation Project of Graduate Students of Jiangsu Province, China under Grants No. CXZZ12_0466, No. CXZZ11_0390the National Natural Science Foundation of China under Grants No. 61071091, No. 61271240, No. 61201160, No. 61172118+2 种基金the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province, China under Grant No. 12KJB510019the Science and Technology Research Program of Hubei Provincial Department of Education under Grants No. D20121408, No. D20121402the Program for Research Innovation of Nanjing Institute of Technology Project under Grant No. CKJ20110006
文摘Video reconstruction quality largely depends on the ability of employed sparse domain to adequately represent the underlying video in Distributed Compressed Video Sensing (DCVS). In this paper, we propose a novel dynamic global-Principal Component Analysis (PCA) sparse representation algorithm for video based on the sparse-land model and nonlocal similarity. First, grouping by matching is realized at the decoder from key frames that are previously recovered. Second, we apply PCA to each group (sub-dataset) to compute the principle components from which the sub-dictionary is constructed. Finally, the non-key frames are reconstructed from random measurement data using a Compressed Sensing (CS) reconstruction algorithm with sparse regularization. Experimental results show that our algorithm has a better performance compared with the DCT and K-SVD dictionaries.
基金supported by the National Natural Science Foundation of China(Nos.11474169 and 61675100)the Tianjin Natural Science Foundation(No.15JCYBJC16900)
文摘In order to improve depth extraction accuracy, a method using moving array lenslet technique(MALT) in pickup stage is proposed, which can decrease the depth interval caused by pixelation. In this method, the lenslet array is moved along the horizontal and vertical directions simultaneously for N times in a pitch to get N sets of elemental images. Computational integral imaging reconstruction method for MALT is taken to obtain the slice images of the 3 D scene, and the sum modulus(SMD) blur metric is taken on these slice images to achieve the depth information of the 3 D scene. Simulation and optical experiments are carried out to verify the feasibility of this method.
