Abstract:
An image processing apparatus comprises a) an input device for inputting color image data which is compression-encoded in a color difference system color space, b) a decoder for decoding the color image data input by the input device, c) a processor for executing correction processing to luminance component data of the color image data decoded by the decoder, and d) an encoder for encoding both the luminance component data processed by the processor, and color difference component data of the color image data output from the decoder. According to another embodiment of the invention, an image processing apparatus is provided which comprises a) an input device for inputting color image data which is compression-encoded in a color difference system color space, b) a decoder for decoding the color image data input by the input device, c) a processor for executing correction processing to luminance component data of the color image data decoded by the decoder, and d) a converter for performing a color space conversion on the basis of the luminance component data processed by the processor, and color difference component data of the color image data output from the decoder.

Description:
BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     The present invention relates to an image processing apparatus and, more particularly, to an image processing apparatus which performs pixel density conversion processing, spatial filtering processing, contrast processing, and the like for color image data. 
     2. Description of the Related Art 
     In conventional image processing apparatuses that perform image editing and image transmission, the image data to be processed are encoded upon storage or transmission, thus realizing reductions of the memory capacity and the transmission data volume. 
     In such conventional image processing apparatus, many encoding schemes of image data have been proposed and put into practical applications. Of such encoding schemes, the method of compressing color image data in the YUV (luminance and color difference) color space by the JPEG (Joint Photographic Experts Group) scheme is well known. 
     Image processing based on JPEG will be briefly described below with reference to FIG.  1 . 
     FIG. 1 is a block diagram for attaining image compression processing based on JPEG. 
     Input image data is divided into (8×8) pixel blocks by a block forming processing unit  101 . 
     The divided image data blocks are DCT (Discrete Cosine Transform)-transformed by a DCT transform processing unit  102 . The DCT-transformed image data blocks are quantized based on a predetermined quantization step in a quantization processing unit  103 , and the quantized blocks are Huffman-encoded by a Huffman encoding processing unit  104 . 
     With the above-mentioned processing, the image data can be compressed to about {fraction (1/10)} without making its image quality deterioration conspicuous. 
     The encoded image data may often be subjected to spatial filtering processing or contrast processing for image display or the like, or pixel density conversion processing for converting the data into a desired resolution or size. 
     Conventionally, the spatial filtering processing, contrast processing, and pixel density conversion processing are performed for R, G, and B signals as primary color signals. 
     Therefore, when the filtering processing or pixel density conversion processing is performed by the conventional method for the image data compression-encoded in the YUV color space by JPEG, or when compression encoding in the YUV color space like JPEG is performed for image data subjected to the filtering processing or pixel density conversion processing by the conventional method, a color space conversion processing unit for converting image signals of the primary color system (R, G, and B signals) into image signals of the color difference system, or vice versa, and an image processing unit for filtering processing are required for each color signal, resulting in complex processing. 
     Furthermore, in order to attain high-quality resolution conversion, a further complex arrangement is required. 
     Therefore, a long processing time is required when such processing is realized by software, or the circuit scale increases when it is realized by hardware, resulting in high cost. 
     SUMMARY OF THE INVENTION 
     It is an object of the present invention to provide, in consideration of the above-mentioned situation, an image processing apparatus and method which can realize simple image processing for already encoded color image data within a short period of time. 
     In order to achieve the above object, according to one preferred aspect of the present invention, an image processing apparatus and method are characterized in that color image data compression-encoded in the color difference system color space is input, the input color image data is decoded, luminance component data of the decoded color image data is subjected to correction processing, and the processed luminance component data and color difference component data of the decoded color image data are encoded. 
     According to one preferred aspect of the present invention, an image processing apparatus and method are characterized in that color image data compression-encoded in the color difference system color space is input, the input color image data is decoded, luminance component data of the decoded color image data is subjected to correction processing, and color space conversion is performed on the basis of the processed luminance component data and color difference component data of the decoded color image data. 
     It is another object of the present invention to provide an image processing apparatus and method, which can realize image processing and compression encoding of input color image data by simple processing within a short period of time. 
     In order to achieve the above object, according to one preferred aspect of the present invention, an image processing apparatus and method are characterized in that color image data is input, the input color image data is converted into data in the color difference system color space, luminance component data of the converted color image data is subjected to correction processing, and the processed luminance component data and color difference component data of the converted color image data are encoded. 
     It is still another object of the present invention to provide an image processing apparatus and method, which can realize high-speed pixel density conversion free from any deterioration of the image quality by changing the degree of image quality after conversion in units of components upon executing the pixel density conversion for color image data. 
     In order to achieve the above object, according to one preferred aspect of the present invention, an image processing apparatus and method are characterized in that color image data is input, first component data of the color image data is subjected to first pixel density conversion processing, second component data of the color image data is subjected to second pixel density conversion processing, and the first pixel density conversion processing can attain pixel density conversion with higher quality than that of the second pixel density conversion processing. 
     Other objects, features and advantages of the invention will become apparent from the following detailed description taken in conjunction with the accompanying drawings. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
     FIG. 1 is a block diagram for realizing image compression processing based on JPEG; 
     FIG. 2 is a block diagram showing the basic arrangement of an image processing apparatus according to the first embodiment of the present invention; 
     FIG. 3 is a block diagram showing in detail the arrangement of a luminance and color difference signals extraction unit  11  of the first embodiment; 
     FIG. 4 is a block diagram showing in detail the arrangement of a luminance and color difference signals storage unit  13  of the first embodiment; 
     FIG. 5 is a block diagram showing the arrangement when the image processing of the present invention is to be realized by software using a digital signal processor (DSP); 
     FIG. 6 is a flow chart showing the operation of the image processing executed by a DSP  42  in the first embodiment; 
     FIG. 7 shows spatial filter coefficients; 
     FIG. 8 shows the reference pixel sequence in spatial filtering processing; 
     FIG. 9 is a block diagram showing in detail the arrangement of a luminance and color difference signals extraction unit  11  according to the second embodiment of the present invention; 
     FIG. 10 is a block diagram showing in detail the arrangement of a luminance and color difference signals storage unit  13  of the second embodiment; 
     FIG. 11 is a flow chart showing the operation of the image processing executed by a DSP  42  in the second embodiment; 
     FIG. 12 is a block diagram showing in detail the arrangement of a luminance and color difference signals extraction unit  11  according to the third embodiment of the present invention; 
     FIG. 13 is a flow chart showing the operation of the image processing executed by a DSP  42  in the third embodiment; 
     FIG. 14 is a block diagram showing in detail the arrangement of a luminance and color difference signals extraction unit  11  according to the fourth embodiment of the present invention; 
     FIG. 15 is a flow chart showing the operation of the image processing executed by a DSP  42  in the fourth embodiment; 
     FIG. 16 is a block diagram showing in detail the arrangement of a luminance and color difference signals storage unit  13  according to the fifth embodiment of the present invention; 
     FIG. 17 is a flow chart showing the operation of the image processing executed by a DSP  42  in the fifth embodiment; 
     FIG. 18 is a block diagram showing the arrangement of an image processing apparatus according to the sixth embodiment of the present invention; 
     FIG. 19 is a block diagram showing in detail the arrangement of a decoding processing unit  202 ; 
     FIG. 20 is a block diagram showing in detail the arrangement of an encoding unit  207 ; 
     FIG. 21 is a flow chart showing pixel density conversion processing in the sixth embodiment; 
     FIG. 22 is a view for explaining the principle of pixel density conversion based on projection in the sixth embodiment; 
     FIG. 23 is a view for explaining the principle of pixel density conversion based on simple thinning-out in the sixth embodiment; and 
     FIG. 24 shows a memory map when the present invention is applied to a recording medium. 
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     FIG. 2 is a block diagram showing the basic arrangement of the first embodiment according to the present invention. Assume that the image data to be processed in the first embodiment is encoded by JPEG, and is stored in a storage device such as a semiconductor memory, a hard disk, or the like. 
     Referring to FIG. 2, a luminance signal color difference signals extraction unit  11  reads out and decodes encoded data stored in the storage device to obtain a luminance (Y) signal and color difference (U, V) signals. 
     Subsequently, an image processing unit  12  performs filtering processing of the Y signal alone obtained by the luminance and color difference signals extraction unit  11 . The Y signal obtained by the image processing unit  12 , and the U and V signals extracted by the luminance and color difference signals extraction unit  11  are stored in the storage device by a luminance and color difference signals storage unit  13 . 
     FIG. 3 is a block diagram showing in detail the luminance and color difference signals extraction unit  11  of the first embodiment. 
     Referring to FIG. 3, an encoded data reading unit  21  reads out image data which is compression-encoded in the YUV color space, and is stored in, e.g., a hard disk, and a Huffman decoding processing unit  22  Huffman-decodes the image data read out by the encoded data reading unit  21 . The decoded image data is inversely quantized by an inverse quantization processing unit  23  to be converted into DCT coefficient data. The inversely quantized image data is subjected to inverse DCT processing by an inverse DCT transform processing unit  24  to be demultiplexed into a Y signal and U and V signals. 
     FIG. 4 is a block diagram showing in detail the luminance and color difference signals storage unit  13  of the first embodiment. 
     Referring to FIG. 4, a Y signal and U and V signals as a luminance signal and color difference signals are DCT-transformed by a DCT transform processing unit  31 , and the transformed signals are quantized by a quantization processing unit  32 . The quantized image data is Huffman-encoded by a Huffman encoding processing unit  33 . The Huffman-encoded image data is stored in a storage device such as a hard disk or the like by an encoded data storing processing unit  34 . 
     FIG. 5 is a block diagram showing the arrangement when the image processing according to the present invention is to be realized using a digital signal processor (DSP). 
     Referring to FIG. 5, an image memory  41  has a plurality of ports, and is used as an image data buffer. The image memory  41  can be accessed by a display control unit, a scanner and print control unit, a microprocessor (MPU) of a total control unit (none of them are shown), a DSP  42  (to be described below), and the like. 
     The DSP  42  executes image processing and the like associated with the present invention in accordance with a program stored in a ROM (Read Only Memory)  44 , and the like. 
     Note that a RAM (Random Access Memory)  43  is used as the work memory of the DSP  42 . 
     An interface unit (i/f)  45  exchanges commands that indicate the operations of the DSP and the like between the DSP  42  and the MPU that controls the total operations. 
     Note that the encoded data to be processed by the image processing is transferred in advance from a storage device such as a hard disk or the like (not shown) to the image memory  41  under the control of the total control unit. 
     The operation flow for executing the image processing of the first embodiment with the arrangement shown in FIG. 5 will be described below with reference to FIG.  6 . 
     In step S 1 , encoded data necessary for the image processing are sequentially read out from the storage device, and the flow advances to step S 2 . 
     In step S 2 , the readout encoded data are Huffman-decoded. The decoded image data are inversely quantized in step S 3 , and the inversely quantized data are inversely DCT-transformed into image data in the YUV color space in step S 4 . 
     In step S 5 , it is checked if the signal of interest is a Y signal. If YES in step S 5 , the flow advances to step S 6 ; otherwise, the flow jumps to step S 7 . 
     In step S 6 , spatial filtering processing is performed for the Y signal. 
     The spatial filtering processing of this embodiment will be described below. 
     FIG. 7 shows spatial filter processing coefficients of this embodiment. FIG. 7 shows filter coefficients used when a Laplacian filter for the purpose of edge emphasis is to be implemented. 
     FIG. 8 shows an example of reference pixels. When filtering processing with the coefficients shown in FIG. 7 is performed for pixel data P 22  in FIG. 8, the pixel value after the processing is obtained by the following equation: 
     
       
           P   22   =P   22 +(4 ×P   22   −P   12   −P   21   −P   23   −P   32 )/4  
       
     
     Returning to the description of the flow in FIG. 6, the Y signal subjected to the filtering processing in step S 6  is DCT-transformed in step S 7 . 
     On the other hand, if U and V signals are determined in step S 5 , these signals are directly DCT-transformed in step S 7 . 
     In step S 8 , quantization processing is executed. Thereafter, image data is Huffman-encoded in step S 9 . 
     In step S 10 , the encoded image data is stored in a storage device such as a hard disk. In step S 11 , it is checked if the above-mentioned processing has been performed for all data. If YES in step S 11 , the flow ends; otherwise, the flow returns to step S 1 . 
     With the above-mentioned processing, the edge emphasis processing can be performed for the compression-encoded image data. 
     As described above, according to this embodiment, spatial filtering processing with sufficiently high quality in practice can be performed for image data which is compression-encoded in the YUV color space by, e.g., JPEG by a simple method within a short period of time. 
     The basic arrangement of an image processing apparatus of the second embodiment is the same as that shown in FIG. 2 as in the first embodiment. 
     In the second embodiment, the arrangements of the luminance and color difference signals extraction unit  11  and the luminance and color difference signals storage unit  13  in FIG. 2 are different from those in the first embodiment, and the image processing unit  12  is the same as that in the first embodiment. 
     In the second embodiment, in order to attain simpler processing than in the first embodiment, the decoding processing of the color difference signals is ended upon the Huffman decoding processing, and the need for the decoding processing of the color difference signals is obviated. 
     FIG. 9 is a block diagram showing in detail the arrangement of the luminance and color difference signals extraction unit  11  in the second embodiment. Note that the same reference numerals in FIG. 9 denote the same parts as in FIG.  3 . 
     Referring to FIG. 9, an encoded data reading unit  21  reads out image data which is compression-encoded in the YUV color space and stored in, e.g., a hard disk or the like, and a Huffman decoding processing unit  22  Huffman-decodes the image data read out by the encoded data reading unit  21 . 
     The decoded image data is demultiplexed into a luminance (Y) signal and color difference (U, V) signals by a demultiplexing processing unit  81  in accordance with a prescribed format. 
     The luminance signal demultiplexed by the demultiplexing processing unit  81  is inversely quantized by an inverse quantization processing unit  82 , and is also inversely DCT-transformed by an inverse DCT transform processing unit  83  to obtain a completely decoded luminance signal. The luminance signal is output to the image processing unit  12 . 
     The color difference signals demultiplexed by the demultiplexing processing unit  81  are directly output to the luminance and color difference signals storage unit  13 . 
     FIG. 10 is a block diagram showing in detail the arrangement of the luminance and color difference signals storage unit  13  of the second embodiment. Note that the same reference numerals in FIG. 10 denote the same parts as in FIG.  4 . 
     Referring to FIG. 10, the luminance signal subjected to the image processing in the image processing unit  12  is DCT-transformed by a DCT transform processing unit  91 , and is quantized by a quantization processing unit  92 . The quantized luminance signal is supplied to a multiplexing processing unit  93 . 
     The multiplexing processing unit  93  multiplexes the luminance signal quantized by the quantization processing unit  92 , and the color difference signals demultiplexed by the demultiplexing processing unit  81  in the luminance and color difference signals extraction unit  11  in accordance with a predetermined format. 
     The image data processed by the multiplexing processing unit  93  is Huffman-encoded by a Huffman encoding processing unit  33 . The Huffman-encoded image data is stored in a storage device such as a hard disk or the like by an encoded data storing processing unit  34 . 
     The processing upon executing the image processing of the second embodiment by software using the arrangement shown in FIG. 5 in the second embodiment as well will be explained below. 
     FIG. 11 is a flow chart showing the operation of the image processing to be executed by a DSP  42  in the second embodiment. 
     In step S 21 , encoded data necessary for the image processing are sequentially read out from the storage device, and the flow advances to step S 22 . 
     In step S 22 , the readout encoded data are Huffman-decoded. In step S 23 , the Huffman-decoded image data are demultiplexed into a Y signal and U and V signals in accordance with the designated format. 
     In step S 24 , it is checked if the signal of interest is a Y signal. If YES in step S 24 , the flow advances to step S 25 ; otherwise, the flow jumps to step S 30 . 
     The Y signal is inversely quantized in step S 25 , and the quantized signal is inversely DCT-transformed in step S 26 . In step S 27 , spatial filtering processing is executed for the Y signal. 
     Note that the same spatial filtering processing as in the first embodiment is performed, and a detailed description thereof will be omitted. 
     The Y signal subjected to the filtering processing in step S 27  is DCT-transformed in step S 28 , and is then quantized in step S 29 . 
     In step S 30 , the Y signal quantized in step S 28  and the U and V signals determined in step S 24  are multiplexed in accordance with a predetermined format. 
     The image data multiplexed in step S 30  is Huffman-coded in step S 31 . 
     In step S 32 , the encoded image data is stored in a storage device such as a hard disk or the like. It is then checked in step S 33  if the above-mentioned processing has been performed for all data. If YES in step S 33 , the flow ends; otherwise, the flow returns to step S 21 . 
     With the above-mentioned processing, the edge emphasis processing can be performed for the compression-encoded image data. 
     As described above, according to this embodiment, spatial filtering processing with sufficiently high quality in practice can be performed for image data which is compression-encoded in the YUV color space by, e.g., JPEG by a simpler method within a shorter period of time than those in the first embodiment. 
     The basic arrangement of an image processing apparatus according to the third embodiment is the same as that shown in FIG. 1 as in the first embodiment. 
     In the third embodiment, the arrangement of only the luminance and color difference signals extraction unit  11  shown in FIG. 2 is different from that in the first embodiment, and other processing units are the same as those in the first embodiment. 
     In the luminance and color difference signals extraction unit  11  in the third embodiment, image signals in the RGB color space read by, e.g., a scanner are subjected to color space conversion to output image signals in the YUV color space. 
     FIG. 12 is a block diagram showing in detail the arrangement of the luminance and color difference signals extraction unit  11  in the third embodiment. 
     An image reading processing unit  101  obtains image signals in the RGB color space using, e.g., an optical scanner. A color space conversion processing unit  102  converts the R, G, and B image signals obtained by the image reading processing unit  101  into image signals in the YUV color space, i.e, a luminance signal and color difference signals. 
     Since the image processing unit  12  and the luminance and color difference signals storage unit  13  are the same as those in the first embodiment, a detailed description thereof will be omitted. 
     The processing upon executing the image processing of the third embodiment by software using the arrangement shown in FIG. 5 in the third embodiment as well will be explained below. 
     FIG. 13 is a flow chart showing the operation of the image processing to be executed by a DSP  42  in the third embodiment. 
     In step S 41 , R, G, and B image signals obtained by an image reading processing unit (not shown; e.g., a scanner) are read. In step S 42 , the read R, G, and B signals are subjected to color space conversion processing to generate Y, U, and V image signals. 
     In the color space conversion processing, the R, G, and B signals are converted into Y, U, and V signals by the following matrix calculations: 
     Y=0.2988×R+0.5869×G+0.1143×B 
     U=0.7130×(R−Y) 
     V=0.5640×(B−Y) 
     In step S 43 , it is checked if the signal of interest is a Y signal. If YES in step S 43 , the flow advance to step S 44 ; otherwise, the flow jumps to step S 45 . 
     In step S 44 , spatial filtering processing is performed for the Y signal. 
     Note that the same spatial filtering processing as in the first embodiment is performed, and a detailed description thereof will be omitted. 
     The Y signal subjected to the filtering processing in step S 44  is DCT-transformed in step S 45 . 
     On the other hand, if the U and V signals are determined in step S 43 , the flow advances to step S 45 , and the U and V signals are directly DCT-transformed. 
     Subsequently, quantization processing is performed in step S 46 , and Huffman-encoding is performed in step S 47 . 
     In step S 48 , the encoded image data is stored in a storage device such as a hard disk or the like. It is then checked in step S 49  if the above-mentioned processing has been performed for all data. If YES in step S 49 , the flow ends; otherwise, the flow returns to step S 41 . 
     As described above, according to the third embodiment, when image data read by, e.g., an image reading device such as a scanner is compressed by JPEG or the like and the compressed data is stored, spatial filtering processing with sufficiently high quality in practice can be performed by a simple method within a short period of time. 
     In the fourth embodiment, the arrangement of only the luminance and color difference signals storage unit  13  is different from that in the first embodiment, and other processing units are the same as those in the first embodiment. 
     In the luminance and color difference signals storage unit  13  of the fourth embodiment, the luminance signal obtained by the image processing unit  12 , and the color difference signals obtained by the luminance and color difference signals extraction unit  11  are converted into image signals in the RGB color space, and the converted signals are displayed on an image display device. 
     FIG. 14 is a block diagram showing the arrangement of the luminance and color difference signals storage unit  11  of the fourth embodiment. 
     A color space conversion processing unit  111  converts Y, U, and V signals into R, G, and B signals. An image display processing unit  112  displays the color-converted R, G, and B signals on an image display device such as a CRT or the like. 
     Since the luminance and color difference signals extraction unit  11  and the image processing unit  12  are the same as those in the first embodiment, a detailed description thereof will be omitted. 
     The processing upon executing the image processing of the fourth embodiment by software using the arrangement shown in FIG. 5 in the fourth embodiment as well will be explained below. 
     FIG. 15 is a flow chart showing the operation of the image processing to be executed by a DSP  42  in the fourth embodiment. 
     In step S 51 , encoded image data required for image processing are sequentially read out from a storage device. The readout encoded data are Huffman-decoded in step S 52 . 
     The Huffman-decoded image data are inversely quantized in step S 53 . 
     The inversely quantized image data are inversely DCT-transformed in step S 54  to extract image data in the YUV color space. 
     It is checked in step S 55  if the signal of interest is a Y signal. If YES in step S 55 , the flow advances to step S 56 ; otherwise, the flow jumps to step S 57 . 
     In step S 56 , spatial filtering processing is performed for the Y signal. 
     Note that the same spatial filtering processing as in the first embodiment is performed, and a detailed description thereof will be omitted. 
     The Y signal subjected to the filtering processing in step S 56 , and the U and V signals extracted by the inverse DCT transform processing are subjected to color space conversion processing in step S 57 . In this processing, the Y, U, and V signals are converted into R, G, and B signals. The color space conversion processing is realized by, e.g., matrix calculations obtained by inverse conversion of RGB signals→YUV signals described in the third embodiment. 
     The R, G, and B signals obtained by the color space conversion processing is transferred to the image display processing unit for controlling, e.g., a CRT in step S 58 . 
     It is then checked in step S 59  if the above-mentioned processing has been performed for all data. If YES in step S 59 , the flow ends; otherwise, the flow returns to step S 51 . 
     As described above, according to this embodiment, when image data which is compressed and stored by, e.g., JPEG is to be displayed on the image display device, spatial filtering processing with sufficiently high quality in practice can be performed by a simple method within a short period of time. 
     In the fifth embodiment, the arrangement of only the luminance and color difference signals storage unit  13  is different from that in the first embodiment, and other processing units are the same as those in the first embodiment. 
     In the luminance and color difference signals storage unit  13  of this embodiment, the luminance signal obtained by the image processing unit  12  and the color difference signals obtained by the luminance and color difference signals extraction unit  11  are converted into image signals in the CMY color space, and the converted image signals are printed by an image print processing unit. 
     FIG. 16 is a block diagram showing in detail the arrangement of the luminance and color difference signals storage unit  13  of the fifth embodiment. 
     A color space conversion processing unit  121  converts Y, U, and V signals into C, M, and Y signals. An image print processing unit  122  prints image data in the CMY color space subjected to the color space conversion using a printer. 
     Since the luminance and color difference signals extraction unit  11  and the image processing unit  12  are the same as those in the first embodiment, a detailed description thereof will be omitted. 
     The processing upon executing the image processing of the fifth embodiment by software using the arrangement shown in FIG. 5 in the fifth embodiment as well will be explained below. 
     FIG. 17 is a flow chart showing the operation of the image processing to be executed by a DSP  42  in the fifth embodiment. 
     In step S 61 , encoded image data required for image processing are sequentially read out from a storage device. The readout encoded image data are Huffman-decoded in step S 62 . 
     The Huffman-decoded image data are inversely quantized in step S 63 . 
     The inversely quantized image data are inversely DCT-transformed in step S 64  to obtain image data in the YUV color space. 
     In step S 65 , it is checked if the signal of interest is a Y signal. If YES in step S 65 , the flow advances to step S 66 ; otherwise, the flow jumps to step S 67 . 
     In step S 66 , spatial filtering processing is performed for the Y signal. 
     Note that the spatial filtering processing is the same as that in the first embodiment. 
     The Y signal subjected to the filtering processing in step S 66 , and U and V signals obtained by the inverse DCT transform processing are subjected to color space conversion processing in step S 67 . In this processing, the Y, U, and V signals are converted into C, M, and Y signals. The color space conversion processing in this case is realized by looking up, e.g., a look-up table which is formed in advance in correspondence with the image display characteristics of a printer. 
     The C, M, and Y signals obtained by the color space conversion are transferred to the image print processing unit for controlling, e.g., a printer in step S 68 . 
     In step S 69 , it is checked if the above-mentioned processing has been performed for all data. If YES in step S 69 , the flow ends; otherwise, the flow returns to step S 61 . 
     As described above, when image data, which is compressed and stored by, e.g., JPEG, is to be subjected to print processing, spatial filtering processing with sufficiently high quality in practice can be performed by a simple method. 
     FIG. 18 is a block diagram showing the basic system arrangement using an image processing apparatus of this embodiment, and illustrates the state wherein an image processing device  200  is connected to a host computer  300 . 
     Image data serving as an original image in the pixel density conversion processing of this embodiment is JPEG-encoded in the host computer  300 , and is transferred to and held in an image memory A  201  in the image processing device  200  in the form of code data. The image memory A  201  comprises, e.g., a semiconductor memory, but may comprise a storage device such as a hard disk or the like. Alternatively, the code data may be stored in an external storage device such as a floppy disk, which may be loaded into the image processing device  200  to implement the image memory A  201 . 
     A decoding processing unit  202  reads out and expands image data in the YUV color space held as the code data in the image memory A  201  so as to obtain Y, U, and V image data. FIG. 19 shows in detail the arrangement of the decoding processing unit  202 , and its operation will be described below. Referring to FIG. 19, the code data held in the image memory A  201  are sequentially read out by a JPEG code data reading unit  217 . The readout code data are Huffman-decoded by a Huffman decoding unit  212  to obtain DCT coefficients. The DCT coefficients are inversely DCT-transformed by an inverse DCT transform unit  213  to reconstruct and output image data in the YUV color space. 
     Referring back to FIG. 18, a first pixel density conversion unit  203  performs pixel density conversion of a luminance signal (Y signal in this case) obtained by the decoding processing unit  202  by processing suffering less image quality deterioration such as projection. On the other hand, a second pixel density conversion unit  204  performs pixel density conversion of color difference signals (U and V signals) obtained by the decoding processing unit  11  by simple processing such as simple thinning-out. Note that the second pixel density conversion unit  204  includes a pixel density conversion unit  205  for the U signal, and a pixel density conversion unit  206  for the V signal. 
     The luminance and color difference signals subjected to the pixel density conversion in the first and second pixel density conversion units  203  and  204  are JPEG-encoded again by an encoding unit  207 , and the encoded data are stored in an image memory B  208 . FIG. 20 shows in detail the arrangement of the encoding unit  207 , and its operation will be described below. Referring to FIG. 20, the Y signal and the U and V signals input to the encoding unit  207  are DCT-transformed by a DCT transform unit  221  to obtain DCT coefficients. The obtained DCT coefficients are Huffman-encoded by a Huffman encoding unit  222  to obtain JPEG code data. The JPEG code data are sequentially stored in the image memory  208  by a JPEG code data storing unit  223 . 
     The above-mentioned image display processing in this embodiment is systematically controlled by a controller  209 . FIG. 21 is a flow chart showing the pixel density conversion processing in the image processing device  200 . 
     When an image pixel density conversion instruction is issued in this embodiment, the controller  209  reads out Y, U, and V code data from the image memory A  201  in step S 71 . The readout code data are subjected to Huffman decoding and inverse DCT transform in the decoding processing unit  202  in step S 72 , thereby reproducing image data in the YUV space from the JPEG code data. 
     It is checked in step S 73  if the decoded data of interest is a Y signal. If YES in step S 73 , the flow advances to step S 74 , and the Y signal is subjected to the pixel density conversion processing based on projection in the first pixel density conversion unit  203 . 
     The basic principle of pixel density conversion method based on the projection method in this embodiment will be explained below with reference to FIG.  22 . For the sake of simplicity, assume that the conversion magnification in each of the main scanning direction and subscanning direction is ⅔, and the number of pixels of the original image is 3×3. 
     A case will be examined below with reference to FIG. 22 wherein an original image  232  consisting of 3×3 pixels is converted into a conversion image  230  of 2×2 pixels. First, the conversion image  230  is projected onto the original image  232 , thus obtaining a projected image  231 . Note that pixels (original pixels) in the original image  232  are indicated by X marks, pixels (conversion pixels) in the conversion image  230  are indicated by ◯, and each pixel has a square region (pixel plane). 
     Let P, Q, R, and S be original pixels having pixel planes that overlap that of a conversion pixel A as the pixel of interest in the projection image  231 . 
     Also, let SP, SQ, SR, and SS be the areas of the pixel planes of the original pixels P, Q, R, and S within the pixel plane of the conversion pixel A projected onto the original image  232 , and IP, IQ, IR, and IS be their pixel values. Then, the mean density IA of the pixel A of interest is given by: 
     
       
           IA =( SP·IP+SQ·IQ+SR·IR+SS·IS )/( SP+SQ+SR+SS )  (1)  
       
     
     The mean density IA obtained in this manner is used as the pixel value of the conversion pixel A upon projection in this embodiment. Note that the original image  232  in this embodiment may be either a binary image or multi-valued image. 
     As is generally known, the pixel density conversion processing based on projection suffers less image quality deterioration among the conventionally proposed pixel density conversion schemes, as described in  Information Processing Society of Japan Transactions , VOL. 26, No. 5. However, the pixel density conversion processing based on projection requires multiplications upon calculating the mean density IA as the conversion pixel value, as can be seen from equation (1) above, and complex arithmetic operations are needed. In this embodiment, the pixel density conversion based on projection, which is complex but can assure high-quality conversion, is performed for only a luminance component signal (Y signal) which has the largest influence on the visual sense characteristics of a human being. 
     That is, reference original pixels (corresponding to the pixel values IP, IQ, IR, and IS shown in FIG. 22) required for calculating the conversion pixel value are read out in step S 74  in FIG.  21 . Subsequently, in step S 75 , the projected areas (corresponding to the areas SP, SQ, SR, and SS shown in FIG. 22) of the original pixel planes included in the pixel plane of the conversion pixel are calculated. In step S 76 , equation (1) above is calculated using the values obtained in steps S 74  and S 75 , thus obtaining the mean density as the pixel value of the conversion pixel. 
     With the processing in steps S 74  to S 76  above, the Y signal has been subjected to the pixel density conversion processing based on projection. 
     On the other hand, if it is determined in step S 73  that the decoded data of interest is not a Y signal, i.e., is a U or V signal, the flow jumps to step S 77 , and the signal is subjected to pixel density conversion processing based on simple thinning-out in the second pixel density conversion unit  204 . 
     The pixel density conversion based on simple thinning-out in this embodiment will be described in detail below with reference to FIG.  23 . In the following description, assume that the conversion magnification in each of the main scanning direction and subscanning direction is ⅔, and the number of pixels of the original image is 3×3 as in the above-mentioned projection. 
     In FIG. 23, hatched pixels of an original image  240  in the main scanning direction and subscanning direction are thinned out to obtain a conversion image  241 . As can be seen from the example shown in FIG. 23, the simple thinning-out processing is the simplest one among various pixel density conversion schemes, but suffers most image quality deterioration of the conversion image. In this embodiment, high-speed pixel density conversion based on a simple method at the cost of image quality is performed for color difference component signals (U and V signals) which experience little influence of image quality deterioration due to conversion on the visual sense characteristics of a human being. 
     Referring back to FIG. 21, Y, U, and V data which have been subjected to the pixel density conversion based on projection or simple thinning-out are subjected to DCT transform and Huffman encoding in the encoding unit  207  in step S 78  to obtain JPEG code data. Thereafter, the JPEG code data are stored in the image memory B  208  in step S 79 . 
     In step S 80 , the above-mentioned processing is performed for all the data to be subjected to pixel density conversion processing stored in the image memory A  201 . 
     As described above, according to this embodiment, when pixel density conversion is performed for image data in the YUV color space, the luminance component is subjected to high-quality conversion, and the color difference components are subjected to simple conversion, thus obtaining a sufficiently high-quality conversion image in practice with a smaller circuit scale without arranging any specific arrangement for color space conversion. 
     In the description of this embodiment, the decoding processing unit  202  decodes JPEG code data to obtain image data (Y, U, and V data) in the YUV color space. However, the present invention is not limited to such specific example. That is, data in other formats such as YIQ data, L*a*b* data, and the like or other encoding schemes may be used or image data which is not encoded may be directly input, as long as image data in the YUV color space can be obtained. 
     In this embodiment, only the luminance component of image data in the YUV color space is subjected to conversion based on projection. However, the present invention is not limited to such specific example. For example, any other conversion methods may be used as long as they suffer less image quality deterioration by pixel density conversion. Similarly, the conversion method for the color difference components is not limited to simple thinning-out, and any other methods may be used as long as they are simple and can attain high-speed processing. That is, various combinations of pixel density conversion methods for the luminance component and color difference components are available in correspondence with the finally required image quality of the conversion image. 
     In the description of this embodiment, the conversion magnification is smaller than 1, i.e., reduction conversion is performed. Of course, the present invention can be applied to enlargement conversion. Even in enlargement conversion, a conversion method that places an importance on image quality can be exploited for the luminance component, and a conversion method that places an importance on the processing speed can be used for the color difference components. 
     In the description of this embodiment, the image data that have been subjected to the pixel density conversion are stored in the image memory B  208 . Of course, the present invention can be applied to an image communication device or the like. In this case, JPEG code data stored in the image memory B  208  need only be sent onto a communication line. Likewise, the JPEG code data that have been subjected to the pixel density conversion can be output to and held in an external storage device or the like. 
     In the sixth embodiment as well, the image processing of the sixth embodiment can be executed in a software manner with the arrangement shown in FIG.  5 . 
     That is, a DSP  42  realizes the processing shown in the flow chart in FIG. 21, i.e., pixel density conversion based on projection for the luminance component and that based on simple thinning-out for the color difference components. The image memory A  201  and the image memory B  208  are assured in an image memory  41  shown in FIG.  5 . 
     Note that the present invention may be applied to either a system made up of a plurality of equipments (e.g., a host computer, an interface device, a reader, a printer, and the like), or an apparatus consisting of a single equipment (e.g., a copying machine, a facsimile apparatus, or the like). 
     The objects of the present invention are also achieved by supplying a storage medium, which records program codes of a software program that can realize the functions of the above-mentioned embodiments to the system or apparatus, and reading out and executing the program codes stored in the storage medium by a computer (or a CPU or MPU) of the system or apparatus, needless to say. 
     In this case, the program codes themselves read out from the storage medium realize the functions of the above-mentioned embodiments, and the storage medium which stores the program codes constitutes the present invention. 
     As the storage medium for supplying the program code, for example, a floppy disk, hard disk, optical disk, magneto-optical disk, CD-ROM, CD-R, magnetic tape, nonvolatile memory card, ROM, and the like may be used. 
     The functions of the above-mentioned embodiments may be realized not only by executing the readout program codes by the computer but also by some or all of actual processing operations executed by an OS (operating system) running on the computer on the basis of an instruction of the program code. 
     Furthermore, the functions of the above-mentioned embodiments may be realized by some or all of actual processing operations executed by a CPU or the like arranged in a function extension board or a function extension unit, which is inserted in or connected to the computer, after the program code read out from the storage medium is written in a memory of the extension board or unit. 
     When the present invention is applied to the storage medium, the storage medium stores program codes corresponding to the above-mentioned flow charts. In this case, the individual modules shown in the memory map in FIG. 24 are stored in the storage medium. That is, the program codes of at least a “luminance and color difference signals input module”, “luminance signal conversion module”, “color difference signal conversion module”, and “luminance and color difference signals output module” can be stored in the storage medium. 
     Note that various other changes and modifications of the present invention may be made without departing from the spirit or principal features of the invention. 
     For example, in the first to fifth embodiments described above, the spatial filtering processing has been exemplified as the contents of image processing. However, the present invention is not limited to such specific processing, but may be applied to any other processing operations such as contrast conversion, as long as they are effective for luminance information of image data. 
     In the first to sixth embodiments described above, the JPEG scheme has been described as the compression scheme of an image signal. However, the present invention is not limited to such specific scheme, and is effective for any other compression schemes expressed in the YUV color space. 
     In the above embodiments, the YUV system is used as the color difference system. However, the present invention is not limited to such specific color system, and for example, a YC b C r  system may be used. 
     In other words, the foregoing description of embodiments has been given for illustrative purposes only and not to be construed as imposing any limitation in every respect. 
     The scope of the invention is, therefore, to be determined solely by the following claims and not limited by the text of the specifications and alterations made within a scope equivalent to the scope of the claims fall within the true spirit and scope of the invention.