1. An apparatus for filtering a sequence of pictures, comprising:
a spatial filter for spatially filtering a picture in the sequence and at least one reference picture selected from among previous pictures and subsequent pictures in the sequence with respect to the picture;
a motion compensator, in signal communication with said spatial filter, for forming, subsequent to spatial filtering, multiple temporal predictions for the picture from the at least one reference picture;
a deblocking filter, in signal communication with said motion compensator, for deblock filtering the multiple temporal predictions; and
a temporal filter, in signal communication with said deblocking filter, for temporally filtering the multiple temporal predictions and combining the multiple temporal predictions to generate a noise reduced version of the picture.
2. The apparatus of claim 1, wherein the multiple temporal predictions are based on correlation with the picture, the picture being an original input picture.
3. The apparatus of claim 1, further comprising an analyzer, in signal communication with said spatial filter, said motion compensator, said deblocking filter, and said temporal filter, for analyzing at least one of textures and edges in the picture and the at least one reference picture with respect to multiple analysis methods,
wherein the multiple temporal predictions are formed, deblock filtered, and temporally filtered, by said motion compensator, said deblocking filter, and said temporal filter, respectively, at least one of which based on at least one of the texture and edge information provided by said analyzer.
4. The apparatus of claim 3, wherein the multiple analysis methods comprise at least one of edge detection, variance analysis, and texture detection.
5. The apparatus of claim 3, wherein said deblocking filter is adapted based upon at least one of correlation with the picture and one or more of the multiple analysis methods, the picture being an original input picture.
6. The apparatus of claim 3, wherein said deblocking filter is adapted based upon at least one of one or more of the multiple analysis methods and correlation with the picture, the picture being an original input picture.
7. The apparatus of claim 3, wherein the multiple analysis methods are used to determine how the one or more temporal predictions are formed by said motion compensator.
8. An apparatus for forming super-resolution pictures from a sequence of pictures, comprising:
a spatial filter for spatially filtering a picture in the sequence and at least one reference picture selected from among previous pictures and subsequent pictures in the sequence with respect to the picture;
a motion compensator, in signal communication with said spatial filter, for forming, subsequent to spatial filtering, multiple temporal predictions for the picture from the at least one reference picture;
a spatial upsampler, in signal communication with said motion compensator, for performing spatial upsampling on the picture and the at least one reference picture;
a deblocking filter, in signal communication with said motion compensator, for deblock filtering the multiple temporal predictions; and
a temporal filter, in signal communication with said deblocking filter, for temporally filtering the multiple temporal predictions and combining the multiple temporal predictions to generate an upsampled version of the picture.
9. The apparatus of claim 8, wherein the multiple temporal predictions are based on correlation with the picture, the picture being an original input picture.
10. The apparatus of claim 8, further comprising an analyzer, in signal communication with said spatial filter, said motion compensator, said deblocking filter, and said temporal filter, for analyzing at least one of textures and edges in the picture and the at least one reference picture with respect to multiple analysis methods,
wherein the multiple temporal predictions are formed, deblock filtered, and temporally filtered, by said motion compensator, said deblocking filter, and said temporal filter, respectively, at least one of which based on at least one of the texture and edge information provided by said analyzer.
11. The apparatus of claim 10, wherein the multiple analysis methods comprise at least one of edge detection, variance analysis, and texture detection.
12. The apparatus of claim 10, wherein said deblocking filter is adapted based upon at least one of one or more of the multiple analysis methods and correlation with the picture, the picture being an original input picture.
13. The apparatus of claim 10, wherein the multiple analysis methods are used to determine how the one or more temporal predictions formed by said motion compensator.
14. A method for filtering a sequence of pictures, comprising:
spatially filtering a picture in the sequence and at least one reference picture selected from among previous pictures and subsequent pictures in the sequence with respect to the picture;
forming, subsequent to spatial filtering, multiple temporal predictions for the picture from the at least one reference picture;
deblock filtering the multiple temporal predictions; and
temporally filtering the multiple temporal predictions and combining the multiple temporal predictions to generate a noise reduced version of the picture, subsequent to said deblock filtering.
15. The method of claim 14, wherein the multiple temporal predictions are based on correlation with the picture, the picture being an original input picture.
16. The method of claim 14, further comprising analyzing at least one of textures and edges in the picture and the at least one reference picture with respect to multiple analysis methods,
wherein the multiple temporal predictions are formed, deblock filtered, and temporally filtered, at least one of which based on at least one of the texture and edge information provided by said analyzing step.
17. The method of claim 16, wherein the multiple analysis methods comprise at least one of edge detection, variance analysis, and texture detection.
18. The method of claim 16, wherein said deblock filtering step is adapted based upon at least one of correlation with the picture and one or more of the multiple analysis methods, the picture being an original input picture.
19. The method of claim 16, wherein said deblock filtering step is adapted based upon at least one of one or more of the multiple analysis methods and correlation with the picture, the picture being an original input picture.
20. The method of claim 16, wherein the multiple analysis methods are used to determine how the one or more temporal predictions are formed by said forming step.
21. A method for forming super-resolution pictures from a sequence of pictures, comprising:
spatially filtering a picture in the sequence and at least one reference picture selected from among previous pictures and subsequent pictures in the sequence with respect to the picture;
forming subsequent to spatial filtering, multiple temporal predictions for the picture from the at least one reference picture;
performing spatial upsampling on the picture and the at least one reference picture;
deblock filtering the multiple temporal predictions; and
temporally filtering the multiple temporal predictions and combining the multiple temporal predictions to generate an upsampled version of the picture, subsequent to said deblock filtering.
22. The method of claim 21, wherein the multiple temporal predictions are based on correlation with the picture, the picture being an original input picture.
23. The method of claim 21, further comprising analyzing at least one of textures and edges in the picture and the at least one reference picture with respect to multiple analysis methods,
wherein the multiple temporal predictions are formed, deblock filtered, and temporally filtered, at least one of which based on at least one of the texture and edge information provided by said analyzing step.
24. The method of claim 23, wherein the multiple analysis methods comprise at least one of edge detection, variance analysis, and texture detection.
25. The method of claim 23, wherein said deblock filtering step is adapted based upon at least one of one or more of the multiple analysis methods and correlation with the picture, the picture being an original input picture.
26. The method of claim 23, wherein the multiple analysis methods are used to determine how the one or more temporal predictions formed by said forming step.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. An insecticidal composition consisting essentially of:
(a) about 45-60 weight percent of a biodegradable carrier;
(b) about 0.9-1.4 weight percent of an ammonium compound;
(c) about 8-12 weight percent of corn steep liquor;
(d) about 18-29 weight percent of invert sugar;
(e) 0.9-1.3 weight percent of Spinosad; and
(f) about 6-11 weight percent of water
where said weight percents are based on the weight of components (a)-(f).
2. A process to apply a composition according to claim 1 said process comprising applying said composition according to claim 1, to an area to control Diptera in an amount sufficient to control such pest.
3. A process according to claim 2 wherein said Diptera is from the family Tephritidae.
4. A process according to claim 2 wherein said Diptera is from the family Drosophilidae.
5. A process according to claim 2 wherein said Diptera is from the family Lonchaeidae.
6. A process according to claim 2 wherein said Diptera is from the family Muscidae.
7. A process according to claim 2 wherein said Diptera is selected from Aedes spp., Agromyza spp., Anastrepha spp., Anopheles spp., Bactrocera spp., Ceratitis spp., Chrysops spp., Cochliomyia spp., Contarinia spp., Culex spp., Dasineura spp., Delia spp., Drosophila spp., Fannia spp., Hylemyia spp., Liriomyza spp., Musca spp., Phorbia spp., Rhagoletis spp., Tabanus spp., and Tipula spp.
8. A process according to claim 2 wherein said Diptera is selected from Agromyza frontella, Anastrepha suspensa, Anastrepha ludens, Anastrepha obliqa, Bactrocera cucurbitae, Bactrocera dorsalis, Bactrocera invadens, Bactrocera zonata, Ceratitis capitata, Dasineura brassicae, Delia platura, Drosophila suzukii, Fannia canicularis, Fannia scalaris, Gasterophilus intestinalis, Gracillia perseae, Haematobia irritans, Hypoderma lineatum, Liriomyza brassicae, Melophagus ovinus, Musca autumnalis, Musca domestica, Oestrus ovis, Oscinella frit, Pegomya betae, Psila rosae, Rhagoletis cerasi, Rhagoletis pomonella, Rhagoletis mendax, Sitodiplosis mosellana, and Stomoxys calcitrans.
9. A process according to claim 2 wherein said Diptera is Ceratitis capitata.