Memory management method and memory management device of image data

Abstract

The invention provides a memory management method and a memory management device of image data. The method comprises the following steps of: A, dividing a memory pool into a data area and an information area, and dividing the data area into data clusters and index clusters; B, judging whether a memory space, which is formed by a first data cluster, in the data area is greater than or equal to the memory space required by data to be stored, if so, executing the step C, otherwise, executing the step D; C, generating linked list nodes in the information area, generating a cluster link in the index clusters of the data area, and executing the step E; D, obtaining the cluster link which is matched with the memory space required by the data to be stored from the index clusters, marking a second data cluster which corresponds to the cluster link as a first identifier in the index clusters, deleting the cluster link and the linked list nodes which are linked with the cluster link, and executing the step B; and E, writing the data to be stored into the second data cluster in the data area. By adoption of the method and the device provided by the invention, generation of fragments can be avoided, and the utilization rate of the memory space and the storage efficiency of the image data are improved.

Description

technical field [0001] The invention relates to image acquisition technology, in particular to a memory management method and device for image data. Background technique [0002] The invention patent with the application number 01118873.1 discloses "adaptive dynamic memory management method", such as figure 1 shown. Combine now figure 1 , the method of above-mentioned invention is described, specifically as follows: [0003] Step 101, check whether there are free fragments in the page cluster of this type of byte fragmentation type, if yes, go to step 105; if not, continue to step 102; step 102, judge whether the ratio of free memory area to the entire memory space is Less than or equal to the set value, if yes, turn to step 104; if no, execute step 103; step 103, draw a corresponding type of page cluster from the free memory area, turn to step 105; step 104, select from other types of page clusters Find out the page clusters in which all the fragments are free, and chan...

AI Technical Summary

Problems solved by technology

Since the existing video surveillance products mostly work in the way of multi-channel forwarding, that is, the data stored in the memory is not released according to the time sequence of storage, but part of the storage space is released according to external instructions or part of the storage space is released randomly. This may cause the free storage space in the memory to be non-continuous. At this time, if the existing adaptive dynamic memory management method is used for management, more fragmentation will not only be generated in the process of saving image data in the free page cluster page clusters, and when large-capacity data is applied for memory storage, the efficiency of finding multiple free shards that support the same type of free page clusters will be greatly reduced

[0007] To sum up, when the existing adaptive dynamic memory management method performs data memory management on the image data collected by the front end of video surveillance products, it may generate more fragmented page clusters, which reduces the utilization of memory space At the same time, there may be a problem of low efficiency in finding free fragments, which further affects the storage efficiency of image data

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