The biometric techniques that identify eye characteristics in a picture include ocular and iris recognition systems. To get a high gratitude performance, such ocular and iris areas need to have a certain picture resolution; otherwise, there is a danger of performance deterioration. These are even more important when using intricate patterns for iris gratitude. The performance of recognition can be improved by acquiring picture of more resolution pictures using techniques like super-resolution reconstruction in scenarios where the acquisition equipment and surroundings cannot be changed and such picture of poor resolution photos are obtained. Previous survey publications, on the other hand, mostly included extensive precises of research on picture of more resolution ocular and iris gratitude. However, they did not do the same for studies on picture of poor resolution ocular and iris gratitude. As a result, we looked at picture of more resolution ocular and iris recognition techniques then described in clarity picture of poor resolution techniques as well as ways to overcome the picture of poor resolution issue. This survey study also highlighted the most recent deep learning-based techniques in detail, while previous survey papers had only focused on and reviewed findings on conventional handmade based on features ocular and iris gratitude.