1. A method of processing an original image, comprising:
generating second data in response to performing at least one discrete wavelet transform (DWT) based upon first data representing the image;
generating third data by combining noise with the second data; and
generating fourth data representing the image by performing a quantization based upon the third data.
2. The method of claim 1 wherein the second data comprises a plurality of subbands and the step of generating third data comprises adding noise to a selected one or more of said subbands.
3. The method of claim 1 further comprising:
generating fifth data in response to entropy encoding based upon the fourth data.
4. The method of claim 1 wherein the noise has a uniform probability density.
5. The method of claim 1 wherein the noise depends upon the content of the original image.
6. The method of claim 1 further comprising:
inverse quantizing based upon the fourth data to generate fifth data;
filtering based upon the fifth data to generate sixth data; and
inverse transforming based upon the sixth data.
7. The method of claim 2 further comprising
inverse quantizing based upon the fourth data to generate fifth data;
filtering based upon the fifth data to generate sixth data; and
inverse transforming based upon the sixth data, wherein the step of filtering comprises low pass filtering a portion of the fifth data corresponding to the selected subband.
8. The method of claim 1 wherein the step of generating second data comprises performing more than one DWT to obtain the second data, each additional DWT being performed upon transform data of a previous DWT.
9. The method of claim 8 further comprising:
inverse quantizing based upon the fourth data to generate fifth data;
filtering based upon the fifth data to generate sixth data; and
inverse transforming based upon the sixth data by performing a number of inverse DWTs that correspond to the DWTs in the step of generating the second data.
10. The method of claim 9 wherein the second data comprises subbands LL2, LH2, HL2, HH2, LH1, HL1, and HH1, and the step of generating third data comprises adding noise to the subband LL2,
and the step of filtering comprises low pass filtering a portion of the fifth data corresponding to the subband LL2.
11. A method comprising:
adjusting inverse quantized image transform data in accordance with noise values to obtain adjusted image data, said inverse quantized data obtained in response to quantization and inverse quantization methodologies performed based upon first transform data, said first transform data obtained in response to at least one discrete wavelet transform performed based upon original image data.
12. The method of claim 11 further comprising
generating second data in response to applying an inverse transformation methodology based on the adjusted data.
13. The method of claim 12 further comprising
applying an encoding method based upon the first transform data prior to applying said inverse quantization.
14. The method of claim 12 further comprising
filtering the adjusted data prior to applying said inverse transformation.
15. An article comprising:
a machine-readable medium having instructions which, when executed by a processor, cause
adding noise to second image transform data to obtain adjusted data, said second data obtained in response to a quantization methodology performed based on first image transform data, said first data obtained in response to at least one discrete wavelet transform performed based upon original image data.
16. The article of claim 15 wherein the machine-readable medium further comprises instructions which, when executed by the processor, further cause
inverse quantizing based upon the first data to obtain the second data; and
inverse transforming based upon the adjusted data.
17. The article of claim 16 wherein the machine-readable medium further comprises instructions which, when executed by the processor, further cause
filtering based upon the adjusted data prior to inverse transforming.
18. The article of claim 15 wherein the machine-readable medium further comprises instructions which, when executed by the processor, further cause
performing a decoding methodology to obtain the second data prior to adding noise.
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. A carbon adsorbent, having the following characteristics:
(a) CO2 capacity greater than 105 ccgram at one bar pressure and temperature of 273\xb0 Kelvin;
(b) CO2 Working Capacity greater than 7.0 weight percent;
(c) CO2 heats of adsorption and desorption each of which is in a range of from 10 to 50 kJmole; and
(d) a CO2N2 Henry’s Law Separation Factor greater than 5.
2. The adsorbent of claim 1, having an average particle diameter greater than 50 \u03bcm.
3. (canceled)
4. The adsorbent of claim 1, comprising particles of diameter in a range of from 150 to 500 \u03bcm.
5. (canceled)
6. The adsorbent of claim 1, having a bulk density greater than 0.55 gmL.
7. The adsorbent of claim 1, having a water adsorptive capacity of less than 5% by weight, based on weight of the adsorbent, at 303\xb0 Kelvin and 40% relative humidity.
8. The adsorbent of claim 1, having porosity characterized by average pore size below 1 nm.
9. The adsorbent of claim 1, having porosity at least 50% of the pore volume of which is constituted by pores in a pore size range of from 0.35 to 0.7 nm.
10. (canceled)
11. The adsorbent of claim 1, having an attrition rate index less than 1 wt %hr as measured by the procedure of ASTM D 5757.
12. The adsorbent of claim 1, having an N2 BET surface area of at least 800 m2 per gram.
13. The adsorbent of claim 1, having an N2 micropore volume of at least 0.2 milliliters per gram.
14. The adsorbent of claim 1, wherein the adsorbent is a pyrolyzate of a PVDC homopolymer or a PVDC copolymer.
15. (canceled)
16. (canceled)
17. (canceled)
18. The adsorbent of claim 1, characterized by CO2 capture recovery of at least 90% and CO2 capture purity of at least 90%, when contacted with a simulated flue gas composition comprising air containing 15% CO2 and saturated with water vapor, at 383\xb0 Kelvin and volumetric flow rate of 100 Lminute of simulated flue gas composition per liter of bed of the adsorbent.
19. The adsorbent of claim 1, characterized by CO2 heats of adsorption and desorption each of which is in a range of from 10 to 50 kJmole.
20. A method of making a carbon material for CO2 capture, said method comprising pyrolyzing a polymeric or copolymeric resin material under conditions that are effective to yield a carbon pyrolyzate material having the following characteristics:
(a) CO2 capacity greater than 105 ccgram at one bar pressure and temperature of 273\xb0 Kelvin;
(b) CO2 Working Capacity greater than 7.0 weight percent;
(c) CO2 heats of adsorption and desorption each of which is in a range of from 10 to 50 kJmole; and
(d) a CO2N2 Henry’s Law Separation Factor greater than 5.
21. The method of claim 20, wherein the resin comprises a PVDC homopolymer or a PVDC copolymer.
22. (canceled)
23. (canceled)
24. (canceled)
25. (canceled)
26. (canceled)
27. (canceled)
28. A CO2 capture apparatus, comprising a carbon adsorbent according to claim 1, arranged for contacting CO2-containing fluid under conditions effecting adsorption of CO2 on the carbon pyrolyzate adsorbent.
29. The CO2 capture apparatus of claim 28, comprising a pressure swing adsorption system, a thermal swing adsorption system, or a vacuum swing adsorption system.
30. (canceled)
31. (canceled)
32. (canceled)
33. The CO2 capture apparatus of claim 28, wherein the apparatus is adapted to regenerate the carbon pyrolyzate adsorbent after it has become at least partially loaded with CO2.
34. A CO2 capture method, comprising contacting a CO2-containing fluid with a carbon adsorbent according to claim 1 under conditions effecting adsorption of CO2 on the carbon pyrolyzate adsorbent.
35. The CO2 capture method of claim 34, further comprising regenerating the carbon pyrolyzate adsorbent after it has become at least partially loaded with CO2.
36. (canceled)