TWI617191B - Method of Image Processing and Device Using the Same - Google Patents
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Abstract
一種影像處理方法，包含有接收一影像並偵測該影像是否為經由一網路所傳輸之動態影像；於偵測出該影像係經由網路所傳輸之動態影像時，偵測傳輸該影像之一傳輸位元率；根據該傳輸位元率從複數個預設銳化增強比率中選擇出一預設銳化增強比率；以及根據所選擇出之該預設銳化增強比率來對該影像進行銳利度優化處理。An image processing method includes: receiving an image and detecting whether the image is a dynamic image transmitted via a network; and detecting the transmission of the image when the image is transmitted through the network; a transmission bit rate; selecting a predetermined sharpening enhancement ratio from the plurality of preset sharpening enhancement ratios according to the transmission bit rate; and performing the image according to the selected preset sharpening enhancement ratio Sharpness optimization processing.
Description
本發明係指一種影像處理方法及其裝置，尤指一種藉由偵測傳輸頻寬來動態選擇影像的優化程度並依據影像大小進行銳利度優化處理的影像處理方法及其裝置。The present invention relates to an image processing method and apparatus thereof, and more particularly to an image processing method and apparatus for dynamically selecting an image optimization degree by detecting a transmission bandwidth and performing sharpness optimization processing according to the image size.
隨著科技的發展與進步，使用者於個人電腦、行動手持裝置瀏覽影像或是經由網路即時瀏覽影片的頻率增加，使用者對於影像的解析度的要求也日漸增加，各種不同處理影像的方法也隨之產生。例如，以單一組的優化參數靜態調整影像的方式，來強化影像邊緣。然而，若是即時性經由網路傳輸的影像影片，由於網路傳輸的速度會隨著時間地點而異，因此，無法透過單一的優化參數靜態調整影像，造成使用者透過網路觀賞影片時，常常會因為解析度不足而影響觀賞時的舒適度。With the development and advancement of technology, the frequency of users browsing images on a personal computer or mobile handheld device or browsing the video through the Internet is increasing, and the user's requirements for image resolution are increasing. Various methods for processing images are widely used. It also comes along. For example, the image edges are enhanced by statically adjusting the image with a single set of optimization parameters. However, in the case of instant video images transmitted over the Internet, since the speed of network transmission varies with time and place, it is not possible to statically adjust the image through a single optimized parameter, which often causes users to watch videos through the Internet. It will affect the comfort of viewing because of insufficient resolution.
因此，如何提供一種動態地調整銳化增強比率，對靜態影像以及即時性影像進行優化，以提供使用者更好的影像解析度及觀賞品質，也就成為業界所努力的目標之一。Therefore, how to dynamically adjust the sharpening enhancement ratio and optimize the still image and the instant image to provide users with better image resolution and viewing quality has become one of the goals of the industry.
因此，本發明之主要目的即在於提供一種影像處理方法及裝置，以有效提升影像的解析度並且提供使用者更舒適的觀賞情境。Therefore, the main object of the present invention is to provide an image processing method and apparatus for effectively improving the resolution of an image and providing a more comfortable viewing environment for the user.
本發明揭露一種影像處理方法，包含有接收一影像並偵測該影像是否為經由一網路所傳輸之動態影像；於偵測出該影像係經由該網路所傳輸之動態影像時，偵測傳輸該影像之一傳輸位元率；根據該傳輸位元率從複數個預設銳化增強比率中選擇出一預設銳化增強比率；以及根據所選擇出之該預設銳化增強比率來對該影像進行銳利度優化處理。The present invention discloses an image processing method, including receiving an image and detecting whether the image is a dynamic image transmitted via a network; and detecting when the image is transmitted through the network; Transmitting a transmission bit rate of the image; selecting a predetermined sharpening enhancement ratio from the plurality of preset sharpening enhancement ratios according to the transmission bit rate; and according to the selected sharpening enhancement ratio selected The image is sharply optimized.
本發明另揭露一種影像處理裝置，包含有一偵測模組，用來接收一影像並偵測該影像是否為經由一網路所傳輸之動態影像，並且於偵測出該影像係經由該網路所傳輸之動態影像時偵測傳輸該影像之一傳輸位元率；一判斷模組，用來根據該傳輸位元率從複數個預設銳化增強比率中選擇出一預設銳化增強比率；以及一優化模組，用來根據所選擇出之該預設銳化增強比率來對該影像進行銳利度優化處理。The invention further discloses an image processing device, comprising a detection module for receiving an image and detecting whether the image is a dynamic image transmitted via a network, and detecting that the image is transmitted through the network The transmitted dynamic image detects and transmits a transmission bit rate of the image; and a determining module is configured to select a preset sharpening enhancement ratio from the plurality of preset sharpening enhancement ratios according to the transmission bit rate And an optimization module for performing sharpness optimization on the image according to the selected sharpening enhancement ratio.
請參考第1圖，第1圖為本發明實施例一影像處理裝置10的示意圖。影像處理裝置10包含一偵測模組102、一計算模組104、一判斷模組106以及一優化模組108。偵測模組102用來接收影像，並偵測載入的一影像是否經由一網路傳輸。計算模組104用來計算出一銳化增強比率（sharpness enhancement ratio）。判斷模組106用來從複數個預設銳化增強比率之中選擇出一預設銳化增強比率。而優化模組108則根據該銳化增強比率或該預設銳化增強比率來對影像進行銳利度優化處理。Please refer to FIG. 1 , which is a schematic diagram of an image processing apparatus 10 according to an embodiment of the present invention. The image processing device 10 includes a detection module 102, a calculation module 104, a determination module 106, and an optimization module 108. The detection module 102 is configured to receive images and detect whether the loaded image is transmitted via a network. The calculation module 104 is used to calculate a sharpness enhancement ratio. The determining module 106 is configured to select a preset sharpening enhancement ratio from among the plurality of preset sharpening enhancement ratios. The optimization module 108 performs sharpness optimization on the image according to the sharpening enhancement ratio or the preset sharpening enhancement ratio.
請參考第2圖，第2圖為本發明實施例一影像處理流程20的示意圖。影像處理流程20可被應用於影像處理裝置10，以執行對應操作。根據影像處理流程20，於步驟200及步驟202中，影像處理裝置10的偵測模組102可接收影像並偵測該影像是否為經由網路所傳輸之動態影像。若是的話，則執行步驟204。舉例來說，於步驟202中，當偵測出所載入的影像為經由網路傳輸，例如經由Youtube、Facebook等網站所播放之動態影片。接著，於步驟204中，偵測模組102可偵測經由網路傳輸該影像之一傳輸位元率（bit rate）或影像解析度。例如，偵測模組102可藉由偵測播放影像所使用應用程式或所瀏覽網站的網址IP位址，偵測其網路傳輸的頻寬來確定其傳輸速度等方式來作為判斷傳輸位元率的依據。偵測模組102亦可根據所使用的瀏覽器之類型來判斷傳輸位元率或是利用任何其他的傳輸位元率偵測方式來判斷傳輸該影像之傳輸位元率。Please refer to FIG. 2 , which is a schematic diagram of an image processing flow 20 according to an embodiment of the present invention. The image processing flow 20 can be applied to the image processing apparatus 10 to perform a corresponding operation. According to the image processing process 20, in step 200 and step 202, the detection module 102 of the image processing device 10 can receive the image and detect whether the image is a dynamic image transmitted via the network. If yes, go to step 204. For example, in step 202, when the detected image is detected as being transmitted via a network, for example, a dynamic movie played on a website such as Youtube or Facebook. Then, in step 204, the detection module 102 can detect a transmission bit rate or image resolution of the image transmitted via the network. For example, the detection module 102 can detect the transmission bit by detecting the IP address of the application used by the image being played or the IP address of the website of the website being browsed, detecting the bandwidth of the network transmission, and determining the transmission speed. The basis of the rate. The detection module 102 can also determine the transmission bit rate according to the type of browser used or use any other transmission bit rate detection method to determine the transmission bit rate of the transmitted image.
於步驟206中，判斷模組106根據該傳輸位元率從複數個預設銳化增強比率中選擇出一預設銳化增強比率，以提供後續影像銳利度優化處理。複數個預設銳化增強比率可以是有關於網路之傳輸位元率。舉例來說，如表一所示，可事先建立對應於不同傳輸位元率與影像解析度之預設銳化增強比率ER1～ER6。當偵測模組102偵測出傳輸該影像之傳輸位元率後，判斷模組106可立即對照表一的配置而選擇出所需之預設銳化增強比率。例如，當偵測模組102偵測出傳輸影像之傳輸位元率為80kbs或影像解析度為144p後，判斷模組106可依據相應之傳輸位元率或影像解析度由表一之預設銳化增強比率ER1～ER6當中選擇出預設銳化增強比率ER1（即x1.55倍）做為後續影像銳利度優化處理之用。如此一來，當載入的影像為經由網路傳輸時將能隨著網路傳輸速度或頻寬的變動而動態地進行銳化調整。 <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td> 影像銳利度優化參數 (影像大小為:1366x768) </td></tr><tr><td> 解析度 </td><td> 傳輸位元率 </td><td> 邊緣數量 </td><td> 銳化比率 </td><td> 強化邊緣數量 (銳化增強比率或預設銳化增強比率) </td></tr><tr><td> 144p </td><td> 80kb/s </td><td> 385953 </td><td> 0.367894 </td><td> 601435 (ER1：x1.55) </td></tr><tr><td> 240p </td><td> 350kb/s </td><td> 395310 </td><td> 0.376813 </td><td> 602454 (ER2：x1.52) </td></tr><tr><td> 360p </td><td> 520kb/s </td><td> 501854 </td><td> 0.478372 </td><td> 604645 (ER3：x1.20) </td></tr><tr><td> 480p </td><td> 830kb/s </td><td> 553587 </td><td> 0.527684 </td><td> 608788 (ER4：x1.10) </td></tr><tr><td> 720p </td><td> 1.6Mb/s </td><td> 597325 </td><td> 0.569375 </td><td> 609434 (ER5：x1.02) </td></tr><tr><td> 1080p </td><td> 3Mb/s </td><td> 609846 </td><td> 0.581311 </td><td> 610004 (ER6：x1.00) </td></tr></TBODY></TABLE>表一 In step 206, the determining module 106 selects a preset sharpening enhancement ratio from the plurality of preset sharpening enhancement ratios according to the transmission bit rate to provide subsequent image sharpness optimization processing. The plurality of preset sharpening enhancement ratios may be related to the transmission bit rate of the network. For example, as shown in Table 1, the preset sharpening enhancement ratios ER1 to ER6 corresponding to different transmission bit rates and image resolutions may be established in advance. After the detection module 102 detects the transmission bit rate of the image, the determination module 106 can immediately select the required preset sharpening enhancement ratio according to the configuration of Table 1. For example, when the detection module 102 detects that the transmission bit rate of the transmitted image is 80 kbs or the image resolution is 144 pp, the determination module 106 can be preset according to the corresponding transmission bit rate or image resolution. Among the sharpening enhancement ratios ER1 to ER6, the preset sharpening enhancement ratio ER1 (ie, x1.55 times) is selected as the subsequent image sharpness optimization processing. In this way, when the loaded image is transmitted via the network, it will be able to dynamically sharpen as the network transmission speed or bandwidth changes. <TABLE border="1" borderColor="#000000" width="85%"><TBODY><tr><td> Image Sharpness Optimization Parameters (image size: 1366x768) </td></tr>< Tr><td> resolution</td><td> transmission bit rate</td><td> number of edges</td><td> sharpening ratio</td><td> number of enhanced edges (sharpening Enhancement ratio or preset sharpening enhancement ratio) </td></tr><tr><td> 144p </td><td> 80kb/s </td><td> 385953 </td><td> 0.367894 </td><td> 601435 (ER1:x1.55) </td></tr><tr><td> 240p </td><td> 350kb/s </td><td> 395310 < /td><td> 0.376813 </td><td> 602454 (ER2:x1.52) </td></tr><tr><td> 360p </td><td> 520kb/s </td ><td> 501854 </td><td> 0.478372 </td><td> 604645 (ER3:x1.20) </td></tr><tr><td> 480p </td><td> 830kb/s </td><td> 553587 </td><td> 0.527684 </td><td> 608788 (ER4:x1.10) </td></tr><tr><td> 720p < /td><td> 1.6Mb/s </td><td> 597325 </td><td> 0.569375 </td><td> 609434 (ER5:x1.02) </td></tr>< Tr><td> 1080p </td><td> 3Mb/s </td><td> 609846 </td><td> 0.581311 </td><td> 610004 (ER6:x1.00) </td ></tr></TBODY></TABLE> Table 1
接著，於步驟214中，優化模組108根據步驟206中所選擇出之預設銳化增強比率或是步驟212中所計算出銳化增強比率來對影像進行影像銳利度優化處理。例如，優化模組108根據所選擇之預設銳化增強比率決定出一增強臨限值，其中優化模組108可依據式（1）計算出相應增強臨限值︰ （1） Next, in step 214, the optimization module 108 performs image sharpness optimization processing on the image according to the preset sharpening enhancement ratio selected in step 206 or the sharpening enhancement ratio calculated in step 212. For example, the optimization module 108 determines an enhancement threshold according to the selected preset sharpening enhancement ratio, wherein the optimization module 108 can calculate the corresponding enhancement threshold according to the formula (1): (1)
其中，TH_E為增強臨限值，E R為步驟206所選擇之預設銳化增強比率或步驟212所計算出之銳化增強比率。 Wherein, TH_E is an enhancement threshold, and E R is a preset sharpening enhancement ratio selected in step 206 or a sharpening enhancement ratio calculated in step 212.
進一步地，優化模組108可將增強臨限值提供至計算模組104，計算模組104根據增強臨限值判斷出影像中之邊緣像素。例如，優化模組108可計算出影像中各像素之梯度值（gradient magnitude）。接著，針對每一像素，可將各像素之梯度值與增強臨限值進行比較，將梯度值大於或等於所述增強臨限值之像素判斷為邊緣像素以及將梯度值小於增強臨限值之像素判斷為非邊緣像素。當計算模組104判斷出影像中哪些像素為邊緣像素後，優化模組108可保留影像中被判斷為邊緣像素之像素以產生一邊緣影像。也就是說，優化模組108濾除影像中被判斷為非邊緣像素之像素以產生邊緣影像。因此，邊緣影像可以是僅顯示原影像中之邊緣像素的影像。最後，優化模組108將該影像與該邊緣影像進行疊加處理以產生一優化影像，以實現影像銳利度優化處理。值得注意的是，在此上述實例中，影像的網路傳輸率及解析度可經由電腦系統軟體或是硬體來偵測並計算得知，具有一對一的對應關係。如此一來，藉由影像處理裝置對影像內容進行優化，以提升影像的解析度，並且提供使用者更優良的視覺效果。Further, the optimization module 108 can provide the enhancement threshold to the calculation module 104, and the calculation module 104 determines the edge pixels in the image according to the enhancement threshold. For example, the optimization module 108 can calculate the gradient magnitude of each pixel in the image. Then, for each pixel, the gradient value of each pixel can be compared with the enhancement threshold, and the pixel whose gradient value is greater than or equal to the enhancement threshold is determined as the edge pixel and the gradient value is less than the enhancement threshold. The pixel is judged to be a non-edge pixel. After the computing module 104 determines which pixels in the image are edge pixels, the optimization module 108 can retain the pixels in the image that are determined to be edge pixels to generate an edge image. That is, the optimization module 108 filters out pixels in the image that are determined to be non-edge pixels to produce an edge image. Therefore, the edge image may be an image that only displays edge pixels in the original image. Finally, the optimization module 108 performs superimposition processing on the image and the edge image to generate an optimized image to implement image sharpness optimization processing. It should be noted that in the above example, the network transmission rate and resolution of the image can be detected and calculated by the computer system software or hardware, and have a one-to-one correspondence. In this way, the image content is optimized by the image processing device to enhance the resolution of the image and provide a better visual effect for the user.
進一步地，當步驟202的判斷結果為否時，則執行步驟208。舉例來說，於步驟202中，當所載入的影像係儲存於電腦的影片或照片時，偵測模組103會偵測出所載入的影像為非經由網路所傳輸。接著，於步驟208中，計算模組104可根據一臨限值計算出影像之邊緣像素數量。例如，計算模組104將影像轉換為灰階影像並且利用梯度公式（式（2）至式（4））來計算影像的邊緣像素數量，梯度公式如下： （2） （3） （4） （5） Further, when the determination result of step 202 is no, step 208 is performed. For example, in step 202, when the loaded image is stored in a movie or photo of the computer, the detecting module 103 detects that the loaded image is transmitted through the network. Next, in step 208, the calculation module 104 can calculate the number of edge pixels of the image according to a threshold value. For example, the computing module 104 converts the image into a grayscale image and uses the gradient formula (Eqs. (2) to (4)) to calculate the number of edge pixels of the image. The gradient formula is as follows: (2) (3) (4) (5)
其中，Gx 1為水平梯度值，Gy 1為垂直梯度值，Gray 1[.][.]為像素灰階值。Magnitude為像素梯度值，Threshold為臨限值，Edge[.][.]為記錄邊緣所在畫素位置之邊緣像素或非邊緣像素，edge為邊緣像素數量。 Where Gx 1 is the horizontal gradient value, Gy 1 is the vertical gradient value, and Gray 1 [.][.] is the pixel grayscale value. Magnitude is the pixel gradient value, Threshold is the threshold value, Edge[.][.] is the edge pixel or non-edge pixel of the pixel position where the edge is recorded, and edge is the number of edge pixels.
具體而言，根據式（2）、式（3）及式（4），利用灰階影像的每一個像素（Pixel）及鄰近像素算出像素梯度值。再根據式（5），將像素梯度值與臨限值進行比較，並將像素梯度值大於或等於臨限值之像素判斷為邊緣像素以及將像素梯度值小於臨限值之像素判斷為非邊緣像素。同時，可計算被判斷為邊緣像素的個數以統計出所有被判斷為邊緣像素的個數（即，邊緣像素數量）。Specifically, according to the equations (2), (3), and (4), the pixel gradient value is calculated using each pixel (Pixel) of the grayscale image and the neighboring pixels. According to the formula (5), the pixel gradient value is compared with the threshold value, and the pixel whose pixel gradient value is greater than or equal to the threshold value is determined as the edge pixel, and the pixel whose pixel gradient value is less than the threshold value is determined as the non-edge. Pixel. At the same time, the number of edge pixels judged as the edge pixels can be calculated to count all the numbers judged as edge pixels (ie, the number of edge pixels).
接著，於步驟210中，計算模組104根據影像的大小（例如，192*144、1366*768等）及影像之邊緣像素數量計算出一銳化比率（Sharpness Ratio）。於步驟212中，計算模組104根據銳化比率計算出影像的銳化增強比率。例如，計算模組104根據式（6）計算出銳化比率，並根據式（7）計算出影像的銳化增強比率。其中式（6）與式（7）如下所示。 （6） （7） Next, in step 210, the calculation module 104 calculates a sharpness ratio according to the size of the image (for example, 192*144, 1366*768, etc.) and the number of edge pixels of the image. In step 212, the calculation module 104 calculates a sharpening enhancement ratio of the image according to the sharpening ratio. For example, the calculation module 104 calculates a sharpening ratio according to the equation (6), and calculates a sharpening enhancement ratio of the image according to the equation (7). Wherein formula (6) and formula (7) are as follows. (6) (7)
其中，S R為銳化比率，edge為邊緣像素數量，Pixel Size為影像的大小，E R為銳化增強比率。 Where S R is the sharpening ratio, edge is the number of edge pixels, Pixel Size is the size of the image, and E R is the sharpening enhancement ratio.
接著，於步驟214中，優化模組108可將上述計算出的銳化增強比率帶入式（1）以求得一增強臨限值TH_E。進一步地，優化模組108可將增強臨限值提供至計算模組104。接著，計算模組104可根據所述增強臨限值判斷出影像中之邊緣像素。例如，計算模組104可根據式（2）、式（3）及式（4）計算出影像中之各像素之梯度值。針對每一像素，計算模組104可根據式（5）將各像素之梯度值與所述增強臨限值比較，並將梯度值大於或等於所述增強臨限值之像素判斷為邊緣像素以及將梯度值小於增強臨限值之像素判斷為非邊緣像素。當計算模組104判斷出影像中哪些像素為邊緣像素後，優化模組108保留影像中被判斷為邊緣像素之像素，以產生一邊緣影像。也就是說，優化模組108濾除影像中被判斷為非邊緣像素之像素以產生邊緣影像，邊緣影像為僅顯示原影像中之邊緣像素之影像。最後，優化模組108將該影像與該邊緣影像進行疊加處理以產生一優化影像，以實現影像銳利度優化處理。Next, in step 214, the optimization module 108 can bring the calculated sharpening enhancement ratio into equation (1) to find an enhancement threshold TH_E. Further, the optimization module 108 can provide an enhancement threshold to the computing module 104. Then, the calculation module 104 can determine the edge pixels in the image according to the enhancement threshold. For example, the calculation module 104 can calculate the gradient values of the pixels in the image according to the equations (2), (3), and (4). For each pixel, the calculation module 104 can compare the gradient value of each pixel with the enhancement threshold according to the formula (5), and determine the pixel whose gradient value is greater than or equal to the enhancement threshold as the edge pixel and A pixel whose gradient value is smaller than the enhancement threshold is judged as a non-edge pixel. After the computing module 104 determines which pixels in the image are edge pixels, the optimization module 108 retains pixels in the image that are determined to be edge pixels to generate an edge image. That is, the optimization module 108 filters out pixels in the image that are determined to be non-edge pixels to generate an edge image, and the edge image is an image that only displays edge pixels in the original image. Finally, the optimization module 108 performs superimposition processing on the image and the edge image to generate an optimized image to implement image sharpness optimization processing.
舉例來說，如第3A圖至第3C圖所示，第3A圖為原始影像，第3B圖為經由增強臨限值TH 2求得的邊緣影像，第3C圖為疊加第3A圖及第3B圖的影像，以對原始影像內容進行優化。由第3C圖可知，藉由第3B圖的邊緣影像，使得圖片更加清晰。如此一來，藉由影像處理裝置的優化處理，將載入的影像內容進行強化，提高影像的解析度，並且提升使用者觀賞時的舒適度。 For example, as shown in FIGS. 3A to 3C, FIG. 3A is an original image, FIG. 3B is an edge image obtained by the enhancement threshold TH 2 , and FIG. 3C is a superimposition 3A and 3B. The image of the image to optimize the original image content. It can be seen from Fig. 3C that the picture is made clearer by the edge image of Fig. 3B. In this way, the image content of the loaded image is enhanced by the optimization processing of the image processing device, the resolution of the image is improved, and the comfort of the user during viewing is improved.
另一方面，影像處理裝置10可事先根據上述式（2）至式（7），計算樣本影像於在不同的網路傳輸位元率或影像解析度之下所對應的預設銳化增強比率，以提供於步驟206之中做為選擇。在一實施例中，若樣本影像於不同的影像解析度與網路傳輸位元率下根據上述式（2）至式（5）所計算出的邊緣數量如表一所示，則可依據樣本影像之影像大小、式（6）與式（7）計算出對應於不同傳輸位元率與影像解析度之預設銳化增強比率，如此一來，於步驟206之中將可依據相應傳輸位元率與影像解析度來即時選取相應的預設銳化增強比率以進行後續銳利度優化處理。在另一實施例中，假設想要將影像細節優化至解析度為1080p時的影像品質時，亦可事先各別設定出預設銳化增強比率ER1～ER6。例如強化邊緣數量可為預設銳化增強比率與邊緣數量的乘積（其中表一之預設銳化增強比率係採小數點第二位後四捨五入法），各強化邊緣數量係相關於解析度為1080p時之邊緣數量，例如各強化邊緣數量大致接近解析度為1080p時之邊緣數量。On the other hand, the image processing apparatus 10 can calculate the preset sharpening enhancement ratio corresponding to the sample image under different network transmission bit rates or image resolutions according to the above formulas (2) to (7). , provided in step 206 as an option. In an embodiment, if the number of edges calculated by the sample image according to the above formulas (2) to (5) at different image resolutions and network transmission bit rates is as shown in Table 1, the sample may be based on the sample. The image size of the image, equations (6) and (7) calculate a preset sharpening enhancement ratio corresponding to different transmission bit rates and image resolutions, so that in step 206, the corresponding transmission bits are available. The rate and image resolution are used to instantly select the corresponding preset sharpening enhancement ratio for subsequent sharpness optimization processing. In another embodiment, if it is desired to optimize the image details to an image quality with a resolution of 1080p, the preset sharpening enhancement ratios ER1 to ER6 may be separately set in advance. For example, the number of enhancement edges can be the product of the preset sharpening enhancement ratio and the number of edges (where the preset sharpening enhancement ratio in Table 1 is rounded off after the second decimal point), and the number of enhancement edges is related to the resolution. The number of edges at 1080p, for example, the number of edges of each enhancement is approximately close to the number of edges at a resolution of 1080p.
需注意的是，前述實施例僅係用以說明本發明之精神，本領域具有通常知識者當可據以作適當之修飾，而不限於此。舉例來說，於步驟208與步驟214中，可利用各種邊緣偵測計算的方式來計算影像的邊緣數量。此外，本發明所述影像可以是全畫面或局部畫面之影像。It is to be noted that the foregoing embodiments are merely illustrative of the spirit of the invention, and those skilled in the art can be modified as appropriate without limitation. For example, in steps 208 and 214, various edge detection calculations may be utilized to calculate the number of edges of the image. In addition, the image of the present invention may be an image of a full picture or a partial picture.
綜上所述，本發明可針對經由網路傳輸之動態影像可隨著網路傳輸速度或頻寬的變動而動態地進行銳化調整，並可計算出合適地銳化增強比率來實現影像銳利度優化處理，進而有效提升影像的解析度並且提供使用者更舒適的觀賞情境。 以上所述僅為本發明之較佳實施例，凡依本發明申請專利範圍所做之均等變化與修飾，皆應屬本發明之涵蓋範圍。In summary, the present invention can dynamically sharpen the dynamic image transmitted through the network as the network transmission speed or bandwidth changes, and can calculate a sharpening enhancement ratio to achieve sharp image. Optimized processing, which effectively improves the resolution of the image and provides a more comfortable viewing environment for the user. The above are only the preferred embodiments of the present invention, and all changes and modifications made to the scope of the present invention should be within the scope of the present invention.
10‧‧‧影像處理裝置10‧‧‧Image processing device
102‧‧‧偵測模組102‧‧‧Detection module
104‧‧‧計算模組104‧‧‧Computation Module
106‧‧‧判斷模組106‧‧‧Judgement module
108‧‧‧優化模組108‧‧‧Optimized modules
20‧‧‧影像處理流程20‧‧‧Image Processing Process
200、202、204、206、208、210、212、214‧‧‧步驟200, 202, 204, 206, 208, 210, 212, 214‧ ‧ steps
第1圖為本發明實施例一影像處理裝置的示意圖。 第2圖為本發明實施例一影像處理流程的示意圖。 第3A圖至第3C圖為本發明實施例一原始影像、一邊緣影像以及優化影像的示意圖。FIG. 1 is a schematic diagram of an image processing apparatus according to an embodiment of the present invention. FIG. 2 is a schematic diagram of an image processing flow according to an embodiment of the present invention. 3A to 3C are schematic diagrams showing an original image, an edge image, and an optimized image according to an embodiment of the present invention.
Claims (20)
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