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A system and method for accurately mapping between image coordinates and geo-coordinates, called geo-spatial registration. The system utilizes the imagery and terrain information contained in the geo-spatial database to precisely align geodetically calibrated reference imagery with an input image, e

A system and method for accurately mapping between image coordinates and geo-coordinates, called geo-spatial registration. The system utilizes the imagery and terrain information contained in the geo-spatial database to precisely align geodetically calibrated reference imagery with an input image, e.g., dynamically generated video images, and thus achieve a high accuracy identification of locations within the scene. When a sensor, such as a video camera, images a scene contained in the geo-spatial database, the system recalls a reference image pertaining to the imaged scene. This reference image is aligned very accurately with the sensor's images using a parametric transformation. Thereafter, other information that is associated with the reference image can easily be overlaid upon or otherwise associated with the sensor imagery.

대표청구항 ▼

A system and method for accurately mapping between image coordinates and geo-coordinates, called geo-spatial registration. The system utilizes the imagery and terrain information contained in the geo-spatial database to precisely align geodetically calibrated reference imagery with an input image, e

A system and method for accurately mapping between image coordinates and geo-coordinates, called geo-spatial registration. The system utilizes the imagery and terrain information contained in the geo-spatial database to precisely align geodetically calibrated reference imagery with an input image, e.g., dynamically generated video images, and thus achieve a high accuracy identification of locations within the scene. When a sensor, such as a video camera, images a scene contained in the geo-spatial database, the system recalls a reference image pertaining to the imaged scene. This reference image is aligned very accurately with the sensor's images using a parametric transformation. Thereafter, other information that is associated with the reference image can easily be overlaid upon or otherwise associated with the sensor imagery. ts obtained as a result of the DCT by using n×n quantization levels included in the quantization table and corresponding to these DCT coefficients and thereby quantizing the DCT coefficients, in the image data decompression means, the de-quantization means inversely quantizes the n×n quantized DCT coefficients of each of the pixel blocks included in the first compressed image data by using n×n quantization levels included in the first quantization table and corresponding to the DCT coefficients, and the inverse conversion means applies inverse discrete cosine transform (IDCT) to n×n DCT coefficients of each of the inversely-quantized pixel blocks to use the n×n IDCT coefficients obtained as a result of the IDCT as the expanded image data, and in the image data compression means, the conversion means applies DCT to n×n IDCT coefficients of each of the pixel blocks included in the generated expanded image data, and the quantization means quantizes n×n DCT coefficients of each of the discrete-cosine-transformed pixel blocks by using quantization levels included in the second quantization table and corresponding to the DCT coefficients to use the n×n quantized DCT coefficients as the second compressed image data. 3. The image data compression apparatus according to claim 1, wherein the quantization index value generation means weights logarithmic values of quantization levels included in the first quantization table and calculates a value by accumulating the weighted logarithmic values to use the value as the quantization index value, and the quantization table generation means generates the second quantization table by changing the quantization levels included in a prepared standard quantization table or the first quantization table so that a value obtained by weighting and accumulating the logarithmic values of the quantization levels included in the standard quantization table or the first quantization table similarly to the case of calculating the quantization index value becomes equal to the changed quantization index value. 4. An apparatus according to claim 3, in which said means for generating a single quantization index value for indexing values of the n×n quantization levels included in a first quantization table correlated to the expanded first compressed image data comprises means for weighting table elements corresponding to a DC component and a low-frequency component with a first weight and table elements corresponding to a high-frequency component with a second weight less than said first weight, whereby DC and low frequency components influence said index value more than high frequency components do. 5. An image data compression method for compressing image data through the JPEG method to generate compressed image data, in which the JPEG method applies discrete cosine transform (DCT) to an image block constituted of n×n pixels constituting image data and quantizes n×n DCT coefficients obtained as a result of the DCT by using any corresponding one of n×n quantization levels included in a quantization table and the compressed image data and the quantized table used to generate the compressed image data are correlated to each other, the method comprising the steps of: expanding first compressed image data generated through the JPEG method to generate expanded image data; generating a single quantization index value for indexing values of the n×n quantization levels included in a first quantization table correlated to the expanded first compressed image data; displaying the expanded image data and the generated quantization index value and changing the displayed generated quantization index value in accordance with input from a user having had an opportunity to observe said expanded image data; setting values of the n×n quantization levels included in the quantization table and generating a second quantization table for the quantization index value same as the changed quantization ind ex value; and compressing the generated expanded image data through the JPEG method by using the generated second quantization table to generate second compressed image data. 6. A method according to claim 5, in which said step of generating a single quantization index value for indexing values of the n×n quantization levels included in a first quantization table correlated to the expanded first compressed image data comprises a step of weighting table elements corresponding to a DC component and a low-frequency component with a first weight and table elements corresponding to a high-frequency component with a second weight less than said first weight, whereby DC and low frequency components influence said index value more than high frequency components do. 7. A recording medium storing a program for compressing image data through a predetermined compression method to generate compressed image data, in which the compression method at least performs compression by using a combination of a plurality of quantization levels (quantization table) and thereby performing quantization and the compressed image data and the quantization table used to generate the compressed image data are correlated to each other, in order to make a computer execute: the image data decompression step of expanding first compressed image data generated through the compression method to generate the expanded image data; the quantization index value generation step of calculating a quantization index value that is calculated by a mathematical function having as inputs the quantization levels included in a first quantization table correlated to the expanded first compressed image data; the display step of displaying the expanded image data and the quantization index value; the quantization index value change step of changing the generated quantization index value to a second index value by a user; the quantization table generation step of generating second quantization table by setting values of the quantization levels included in the quantization table in accordance with the changed quantization index values to generate a second quantization table having an index equal to said second index value; and the image data compression step of compressing the generated expanded image data through the compression method by using the generated second quantization table to generate second compressed image data that is not constrained to fit within a reference storage amount. 8. The recording medium according to claim 7, wherein the compression method applies a predetermined conversion to the image data every pixel block including a plurality of pixels and compressing coefficients obtained as a result of the conversion by using each quantization level included in the quantization table and corresponding to each of the coefficients and thereby quantizing the coefficients, the image data decompression step includes the de-quantization for inversely quantizing the pixel blocks included in the first compressed image data by using the first quantization table and the inverse conversion for applying the conversion opposite to the predetermined conversion to the inversely-quantized pixel blocks to generate the expanded image data, the quantization index value change step changes the generated quantization index values in accordance with external operations, and the image data compression step includes the conversion for applying the predetermined conversion to the pixel blocks included in the generated expanded image data and the quantization for quantizing the converted pixel blocks by using the generated second quantization table to generate the second compressed image data. 9. The recording medium according to claim 8, wherein the compression method compresses the image data by applying discrete cosine transform (DCT) to the data every pixel block including n×n pixels and quantizing n×n DCT coefficients obtained as a result of the DCT by using n×n